# Best Big Data Integration Platforms ## How Many Big Data Integration Platforms Products Does G2 Track? **Total Products under this Category:** 130 ### Category Stats (Aug 2026) - **Average Rating:** 4.51/5 The average rating of products in this category, based on all submitted ratings - **Top Trending Product:** Control-M (+0.51%) - Among all products in this category, Control-M recorded the largest rating increase compared to last month _Last updated: August 07, 2026_ ## How Does G2 Rank Big Data Integration Platforms Products? **Why You Can Trust G2's Software Rankings:** - 30 Analysts and Data Experts - 10,300+ Authentic Reviews - 130+ Products - Unbiased Rankings G2's software rankings are built on verified user reviews, rigorous moderation, and a consistent research methodology maintained by a team of analysts and data experts. Each product is measured using the same transparent criteria, with no paid placement or vendor influence. While reviews reflect real user experiences, which can be subjective, they offer valuable insight into how software performs in the hands of professionals. Together, these inputs power the G2 Score, a standardized way to compare tools within every category. ## G2 Grid® for Big Data Integration Platforms ![G2 Grid® for Big Data Integration Platforms plotting products by satisfaction and market presence](https://www.g2.com/categories/big-data-integration-platforms/grids.png?focus%5B%5D=6073&focus%5B%5D=989&focus%5B%5D=10938&focus%5B%5D=23920&focus%5B%5D=15884&focus%5B%5D=52204&focus%5B%5D=2975&focus%5B%5D=87449) Highlighted products: Google Cloud BigQuery, Alteryx, Snowflake, Fivetran, Workato, Azure Data Factory, SnapLogic Intelligent Integration Platform (IIP), and AWS Lake Formation. Underlying data: [Grid® JSON](https://www.g2.com/categories/big-data-integration-platforms/grids.json?focus%5B%5D=google-cloud-bigquery&focus%5B%5D=alteryx&focus%5B%5D=snowflake&focus%5B%5D=fivetran&focus%5B%5D=workato&focus%5B%5D=azure-data-factory&focus%5B%5D=snaplogic-intelligent-integration-platform-iip&focus%5B%5D=aws-lake-formation) **Sponsored** ### SAP Integration Suite SAP Integration Suite (formerly SAP Cloud Platform Integration Suite) is an integration platform as a service (iPaaS) that allows the user to integrate on-premise and cloud-based applications and processes with tools and prebuilt content managed by SAP. With SAP Integration Suite, you can become future ready and scale up your integration capabilities to connect and contextualize experiences for customers, partners, and employees across the enterprise and extended ecosystems. [Visit website](https://www.g2.com/external_clickthroughs/record?secure%5Bad_program%5D=ppc&secure%5Bad_slot%5D=category_product_list_llm&secure%5Bcategory_id%5D=1186&secure%5Bchosen_at%5D=2026-08-15T09%3A20%3A22Z&secure%5Bdisplayable_resource_id%5D=1186&secure%5Bdisplayable_resource_type%5D=Category&secure%5Bmedium%5D=sponsored&secure%5Bplacement_reason%5D=page_category&secure%5Bplacement_resource_ids%5D%5B%5D=1186&secure%5Bprioritized%5D=false&secure%5Bproduct_id%5D=6306&secure%5Bresource_id%5D=1186&secure%5Bresource_type%5D=Category&secure%5Bsource_type%5D=category_page&secure%5Bsource_url%5D=https%3A%2F%2Fwww.g2.com%2Fcategories%2Fbig-data-integration-platforms&secure%5Btoken%5D=49a73ec9515c969ad8ffaabf7757b6fcc38fa0ab4c29a09d6cef71bdedd9f06e&secure%5Burl%5D=https%3A%2F%2Fwww.sap.com%2Fcmp%2Fdg%2Fcommon-integration-challenges%2Findex.html%3Fcampaigncode%3DCRM-YJ25-BTP-408007%26source%3DINTEGRATION-click-campaign-G2&secure%5Burl_type%5D=custom_url) ### [Google Cloud BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews) BigQuery is an AI-ready, petabyte-scale, and cost-effective data warehouse that lets you run analytics over vast amounts of data in near real time. Store 10 GiB of data and run up to 1 TiB of queries for free per month. **Average Rating:** 4.5/5.0 **Total Reviews:** 1,145 #### How Do G2 Users Rate Google Cloud BigQuery? - **Has the product been a good partner in doing business?:** 8.6/10 (Category avg: 8.9/10) - **Quality of Support:** 8.3/10 (Category avg: 8.9/10) - **Ease of Use:** 8.7/10 (Category avg: 8.9/10) - **Ease of Admin:** 8.5/10 (Category avg: 8.5/10) #### Who Is the Company Behind Google Cloud BigQuery? - **Seller:** [Google](https://www.g2.com/sellers/google) - **Year Founded:** 1998 - **HQ Location:** Mountain View, CA - **Twitter:** @google 31,899,995 Twitter followers - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=fe4a5936665c9702418dd53c477fef5a7baea08078bb117ed67e966fc581b9ec&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F1441%2F&secure%5Burl_type%5D=linkedin_company_website) 341,888 employees on LinkedIn® - **Ownership:** NASDAQ:GOOG #### Who Uses This Product? - **Who Uses This:** Data Engineer, Data Analyst - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 38% Large, 35% Medium #### What Do G2 Reviewers Say About Google Cloud BigQuery? _AI-generated summary from verified user reviews_ ##### Pros - Users appreciate the **ease of use** of Google Cloud BigQuery, enabling quick analysis of massive datasets without hassle. - Users appreciate the **exceptional speed** of BigQuery, allowing for quick processing of large datasets seamlessly. - Users love the **easy integration** with Google Cloud services, enabling smooth data analysis and management. - Users appreciate the **fast querying capabilities** of Google Cloud BigQuery, allowing effortless analysis of massive datasets. - Users appreciate the **query efficiency** of BigQuery, effortlessly processing complex queries on massive datasets with speed. ##### Cons - Users find the **costs can escalate quickly** with Google Cloud BigQuery, requiring careful query optimization to manage expenses. - Users struggle with **query issues** in BigQuery, facing rising costs and challenges in query optimization and troubleshooting. - Users find **cost management challenging** with Google Cloud BigQuery due to unpredictable pricing and incidents of unexpected charges. - Users experience **cost issues** with Google Cloud BigQuery, struggling with unexpected high bills and limited pricing visibility. - Users find the **steep learning curve** of Google Cloud BigQuery challenging, particularly for advanced features and optimization techniques. #### What Are Recent G2 Reviews of Google Cloud BigQuery? **["Easy-to-Use Cloud Tool with Shareable, Saved Queries"](https://www.g2.com/survey_responses/google-cloud-bigquery-review-12958418)** **Rating:** 4.0/5.0 stars _— Reetika P._ [Read full review](https://www.g2.com/survey_responses/google-cloud-bigquery-review-12958418) **["Scalable, Secure BigQuery That Connects Seamlessly Across Services"](https://www.g2.com/survey_responses/google-cloud-bigquery-review-12638747)** **Rating:** 5.0/5.0 stars _— Aayush M._ [Read full review](https://www.g2.com/survey_responses/google-cloud-bigquery-review-12638747) #### What Are G2 Users Discussing About Google Cloud BigQuery? - [Is Big Query free?](https://www.g2.com/discussions/is-big-query-free) - 3 comments, 1 upvote - [Is BigQuery part of Google Cloud Platform?](https://www.g2.com/discussions/is-bigquery-part-of-google-cloud-platform) - 2 comments, 2 upvotes - [What is Google BigQuery based on?](https://www.g2.com/discussions/what-is-google-bigquery-based-on) - 1 comment - [What is Google BigQuery used for?](https://www.g2.com/discussions/what-is-google-bigquery-used-for) - 1 comment ### [Alteryx](https://www.g2.com/fr/products/alteryx/reviews) Alteryx, grâce à sa plateforme Alteryx One, aide les entreprises à transformer des données complexes et déconnectées en un état propre et prêt pour l'IA. Que vous créiez des prévisions financières, analysiez la performance des fournisseurs, segmentiez des données clients, analysiez la rétention des employés ou construisiez des applications d'IA compétitives à partir de vos données propriétaires, Alteryx One facilite le nettoyage, le mélange et l'analyse des données pour débloquer les insights uniques qui conduisent à des décisions percutantes. Analytique guidée par l'IA Alteryx automatise et simplifie chaque étape de la préparation et de l'analyse des données, de la validation et de l'enrichissement à l'analytique prédictive et aux insights automatisés. Intégrez l'IA générative directement dans vos flux de travail pour rationaliser les tâches complexes de données et générer des insights plus rapidement. Une flexibilité inégalée, que vous préfériez des flux de travail sans code, des commandes en langage naturel ou des options à faible code, Alteryx s'adapte à vos besoins. Fiable. Sécurisé. Prêt pour l'entreprise. Alteryx est approuvé par plus de la moitié des Global 2000 et 19 des 20 plus grandes banques mondiales. Avec une automatisation, une gouvernance et une sécurité intégrées, vos flux de travail peuvent évoluer et maintenir la conformité tout en fournissant des résultats cohérents. Et peu importe si vos systèmes sont sur site, hybrides ou dans le cloud ; Alteryx s'intègre sans effort dans votre infrastructure. Facile à utiliser. Profondément connecté. Ce qui distingue vraiment Alteryx, c'est notre concentration sur l'efficacité et la facilité d'utilisation pour les analystes et notre communauté active de 700 000 utilisateurs d'Alteryx pour vous soutenir à chaque étape de votre parcours. Avec une intégration transparente aux données partout, y compris des plateformes comme Databricks, Snowflake, AWS, Google, SAP et Salesforce, notre plateforme aide à unifier les données cloisonnées et à accélérer l'accès aux insights. Visitez Alteryx.com pour plus d'informations et pour commencer votre essai gratuit. **Average Rating:** 4.6/5.0 **Total Reviews:** 861 #### How Do G2 Users Rate Alteryx? - **the product a-t-il été un bon partenaire commercial?:** 8.8/10 (Category avg: 8.9/10) - **Qualité du support:** 8.5/10 (Category avg: 8.9/10) - **Facilité d’utilisation:** 8.7/10 (Category avg: 8.9/10) - **Facilité d’administration:** 8.3/10 (Category avg: 8.5/10) #### Who Is the Company Behind Alteryx? - **Vendeur:** [Alteryx](https://www.g2.com/fr/sellers/alteryx) - **Site Web de l'entreprise:** www.alteryx.com - **Année de fondation:** 1997 - **Emplacement du siège social:** Irvine, CA - **Twitter:** @alteryx 26,149 abonnés Twitter - **Page LinkedIn®:** [www.linkedin.com](https://www.g2.com/fr/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=ae8a7629c5a6d593caff29361a6ee3fb670df11992dd94a9656c66461078b340&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F903031%2F&secure%5Burl_type%5D=linkedin_company_website) 2,304 employés sur LinkedIn® #### Who Uses This Product? - **Who Uses This:** Analyste de données, Analyste - **Top Industries:** Services financiers, Comptabilité - **Company Size:** 63% Large, 21% Medium #### What Do G2 Reviewers Say About Alteryx? _AI-generated summary from verified user reviews_ ##### Pros - Les utilisateurs apprécient la **facilité d'utilisation** d'Alteryx, le trouvant convivial et efficace pour les utilisateurs non techniques. - Les utilisateurs apprécient les **capacités d'automatisation** d'Alteryx, améliorant la rapidité et l'efficacité dans la préparation et l'analyse des données. - Les utilisateurs adorent le **design intuitif** d'Alteryx, rendant la gestion des données et la création de flux de travail sans effort et efficace. - Les utilisateurs trouvent qu'Alteryx est **très facile à apprendre et à utiliser** , améliorant ainsi leur flux de travail et leur expérience d'automatisation des données. - Les utilisateurs apprécient l' **efficacité** d'Alteryx, permettant un traitement rapide des données et des flux de travail simplifiés sans codage complexe. ##### Cons - Les utilisateurs mentionnent qu'Alteryx a un **coût élevé** qui peut être un défi pour les petites équipes et les startups. - Les utilisateurs trouvent une **courbe d'apprentissage abrupte** pour les fonctionnalités avancées, ce qui rend difficile pour les débutants de maîtriser Alteryx rapidement. - Les utilisateurs soulignent les **fonctionnalités manquantes** dans Alteryx, telles que les connecteurs limités et les problèmes de flexibilité de sortie. - Les utilisateurs trouvent **des difficultés d'apprentissage** dans Alteryx en raison d'outils déroutants et d'erreurs de dépannage, surtout pour les débutants. - Les utilisateurs rencontrent une **performance lente** lors du traitement de grands ensembles de données, ce qui affecte l'efficacité et la convivialité dans Alteryx. #### What Are Recent G2 Reviews of Alteryx? **["Rend la préparation des données plus rapide avec un flux de travail intuitif de glisser-déposer"](https://www.g2.com/fr/survey_responses/alteryx-review-13190742)** **Rating:** 4.5/5.0 stars _— Anushka S._ [Read full review](https://www.g2.com/fr/survey_responses/alteryx-review-13190742) **["Échelles les opérations et économise du temps avec des flux de travail de données automatisés"](https://www.g2.com/fr/survey_responses/alteryx-review-13047637)** **Rating:** 4.5/5.0 stars _— Ihor B._ [Read full review](https://www.g2.com/fr/survey_responses/alteryx-review-13047637) ### [Snowflake](https://www.g2.com/fr/products/snowflake/reviews) Snowflake permet à chaque organisation de mobiliser leurs données avec le AI Data Cloud de Snowflake. Les clients utilisent le AI Data Cloud pour unir des données cloisonnées, découvrir et partager des données en toute sécurité, alimenter des applications de données et exécuter divers charges de travail d'IA/ML et d'analytique. Où que se trouvent les données ou les utilisateurs, Snowflake offre une expérience de données unique qui s'étend sur plusieurs clouds et géographies. Des milliers de clients dans de nombreuses industries, y compris 691 des 2000 plus grandes entreprises mondiales de Forbes en 2023 (G2K) au 31 janvier, utilisent le AI Data Cloud de Snowflake pour dynamiser leurs entreprises. **Average Rating:** 4.5/5.0 **Total Reviews:** 713 #### How Do G2 Users Rate Snowflake? - **the product a-t-il été un bon partenaire commercial?:** 9.0/10 (Category avg: 8.9/10) - **Qualité du support:** 8.7/10 (Category avg: 8.9/10) - **Facilité d’utilisation:** 9.0/10 (Category avg: 8.9/10) - **Facilité d’administration:** 8.7/10 (Category avg: 8.5/10) #### Who Is the Company Behind Snowflake? - **Vendeur:** [Snowflake, Inc.](https://www.g2.com/fr/sellers/snowflake-inc) - **Site Web de l'entreprise:** www.snowflake.com - **Année de fondation:** 2012 - **Emplacement du siège social:** 135 Constitution Drive, Menlo Park CA - **Twitter:** @SnowflakeDB 278 abonnés Twitter - **Page LinkedIn®:** [www.linkedin.com](https://www.g2.com/fr/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=ad18ff73a9b8bb34dd1b98a6ba1c6be57f7364939ad352612ecc483aba05d2b2&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fsnowflake-computing%2F&secure%5Burl_type%5D=linkedin_company_website) 11,308 employés sur LinkedIn® #### Who Uses This Product? - **Who Uses This:** Ingénieur de données, Analyste de données - **Top Industries:** Technologie de l'information et services, Logiciels informatiques - **Company Size:** 45% Medium, 43% Large #### What Do G2 Reviewers Say About Snowflake? _AI-generated summary from verified user reviews_ ##### Pros - Les utilisateurs apprécient la **facilité d'utilisation** de Snowflake, le trouvant rapide et efficace pour le partage de données et l'analyse. - Les utilisateurs apprécient les **fonctionnalités fiables** de Snowflake, profitant de son interface intuitive et de son intégration de données transparente pour l'analyse. - Les utilisateurs trouvent que les **capacités de gestion des données** de Snowflake sont excellentes pour agréger et interroger efficacement plusieurs ensembles de données. - Les utilisateurs admirent la **scalabilité transparente** de Snowflake, qui s'adapte sans effort aux exigences de travail et assure des performances optimales. - Les utilisateurs apprécient la **rapidité de l'analyse des données** de Snowflake, permettant des insights rapides sans soucis d'infrastructure. ##### Cons - Les utilisateurs trouvent que les **coûts élevés** de Snowflake sont lourds, surtout pour les petites entreprises avec des budgets limités. - Les utilisateurs trouvent des **limitations de fonctionnalités** dans Snowflake, telles que l'absence de blocs de code et des difficultés dans la gestion des autorisations. - Les utilisateurs constatent que la **gestion des coûts** nécessite de la discipline, car des frais inattendus peuvent s'accumuler rapidement sans surveillance attentive. - Les utilisateurs trouvent la **structure des coûts difficile à optimiser** , ce qui entraîne des dépenses initiales plus élevées que prévu lors de la mise en œuvre. - Les utilisateurs trouvent que les **fonctionnalités limitées** de Snowflake dans les scripts dynamiques et la surveillance entravent la flexibilité et l'utilisabilité. #### What Are Recent G2 Reviews of Snowflake? **["Mise à l'échelle élastique et analyses rapides avec Snowflake"](https://www.g2.com/fr/survey_responses/snowflake-review-13129003)** **Rating:** 4.5/5.0 stars _— Ravindra N._ [Read full review](https://www.g2.com/fr/survey_responses/snowflake-review-13129003) **["Snowflake simplifie la gestion des données à grande échelle"](https://www.g2.com/fr/survey_responses/snowflake-review-12898129)** **Rating:** 4.0/5.0 stars _— Harshil A._ [Read full review](https://www.g2.com/fr/survey_responses/snowflake-review-12898129) #### What Are G2 Users Discussing About Snowflake? - [What is Snowflake used for?](https://www.g2.com/fr/discussions/what-is-snowflake-used-for) - 2 comments, 1 upvote ### [Fivetran](https://www.g2.com/fr/products/fivetran/reviews) Fivetran est la fondation de données pour l'IA. Une plateforme unique déplace, gère et transforme les données de chaque application, base de données, flux d'événements et fichier sur lesquels votre entreprise fonctionne en une fondation gouvernée sur laquelle les analyses, les opérations et l'IA peuvent agir. Les connecteurs se déploient en quelques minutes, fonctionnent de manière autonome et s'ajustent automatiquement lorsqu'une source change, de sorte que votre équipe de données passe son temps à construire, et non à maintenir des pipelines. **Average Rating:** 4.3/5.0 **Total Reviews:** 808 #### How Do G2 Users Rate Fivetran? - **the product a-t-il été un bon partenaire commercial?:** 8.6/10 (Category avg: 8.9/10) - **Qualité du support:** 8.5/10 (Category avg: 8.9/10) - **Facilité d’utilisation:** 9.0/10 (Category avg: 8.9/10) - **Facilité d’administration:** 8.8/10 (Category avg: 8.5/10) #### Who Is the Company Behind Fivetran? - **Vendeur:** [Fivetran](https://www.g2.com/fr/sellers/fivetran) - **Site Web de l'entreprise:** www.fivetran.com - **Année de fondation:** 2012 - **Emplacement du siège social:** Oakland, CA - **Twitter:** @fivetran 5,767 abonnés Twitter - **Page LinkedIn®:** [www.linkedin.com](https://www.g2.com/fr/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=7f1ca0a984cd3b7fe678e6cf023235ee7978629644faf3910a5df7f92b63eea3&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Ffivetran%2F&secure%5Burl_type%5D=linkedin_company_website) 1,848 employés sur LinkedIn® #### Who Uses This Product? - **Who Uses This:** Ingénieur de données, Analyste de données - **Top Industries:** Logiciels informatiques, Technologie de l'information et services - **Company Size:** 59% Medium, 27% Small #### What Do G2 Reviewers Say About Fivetran? _AI-generated summary from verified user reviews_ ##### Pros - Les utilisateurs apprécient la **facilité d'utilisation** de Fivetran, profitant d'une intégration transparente et d'une maintenance sans effort après l'installation. - Les utilisateurs apprécient la **configuration facile** de Fivetran, ce qui le rend simple à intégrer avec les applications existantes. - Les utilisateurs apprécient la **facilité d'intégration** de Fivetran, permettant une connectivité transparente avec diverses applications et outils. - Les utilisateurs apprécient le **support client réactif** de Fivetran, ce qui améliore leur expérience globale et leur satisfaction. - Les utilisateurs apprécient la **mise en page intuitive et simple** de Fivetran, rendant la gestion des données sans effort et agréable. ##### Cons - Les utilisateurs rencontrent des **problèmes de synchronisation** avec des échecs sporadiques et une confusion concernant les quotas d'utilisation, compliquant leur flux de travail. - Les utilisateurs notent que le prix de Fivetran est **assez cher** , ce qui limite l'accessibilité pour de nombreux utilisateurs potentiels. - Les utilisateurs rencontrent des **problèmes d'intégration** avec Fivetran, notamment en ce qui concerne la propriété du schéma et la modification efficace des connexions. - Les utilisateurs trouvent que la **, nécessitant des connaissances techniques significatives pour naviguer efficacement dans le système au départ.** - Les utilisateurs considèrent les **problèmes de tarification** de Fivetran comme un obstacle, souhaitant des coûts plus bas et des options plus flexibles pour l'accessibilité. #### What Are Recent G2 Reviews of Fivetran? **["Pipelines sans code et auto-surveillants avec des connecteurs qui fonctionnent simplement"](https://www.g2.com/fr/survey_responses/fivetran-review-13137995)** **Rating:** 5.0/5.0 stars _— Umesh ._ [Read full review](https://www.g2.com/fr/survey_responses/fivetran-review-13137995) **["Intégrations de données sans code rapides et fiables avec un énorme retour sur investissement"](https://www.g2.com/fr/survey_responses/fivetran-review-13138238)** **Rating:** 4.5/5.0 stars _— Jose Maria P._ [Read full review](https://www.g2.com/fr/survey_responses/fivetran-review-13138238) #### What Are G2 Users Discussing About Fivetran? - [What is Fivetran used for?](https://www.g2.com/fr/discussions/fivetran-what-is-fivetran-used-for) - 1 comment - [À quoi sert le recensement ?](https://www.g2.com/fr/discussions/what-is-census-used-for) - [Who owns Fivetran?](https://www.g2.com/fr/discussions/who-owns-fivetran) - [Combien coûte Fivetran ?](https://www.g2.com/fr/discussions/how-much-does-fivetran-cost) - 1 comment - [Fivetran est-il un outil ETL ?](https://www.g2.com/fr/discussions/is-fivetran-an-etl-tool) - 2 comments ### [Workato](https://www.g2.com/fr/products/workato/reviews) Workato est la plateforme iPaaS la mieux notée et le leader en MCP d'entreprise — la plateforme de confiance des entreprises pour unifier l'intégration, l'automatisation et l'IA dans un environnement d'exécution sécurisé et natif du cloud. Fié par plus de 12 000 clients, dont la moitié du Fortune 500, Workato connecte chaque système, processus et source de données avec plus de 14 000 connecteurs préconstruits. Ce qui distingue Workato : l'Enterprise MCP transforme les processus commerciaux éprouvés en compétences prêtes à l'emploi et régies que tout agent IA — Claude, ChatGPT, Cursor ou construit sur mesure — peut exécuter en toute sécurité et de manière prévisible. Aucun remplacement complet nécessaire. Que ce soit pour moderniser les intégrations héritées ou déployer l'IA agentique à grande échelle, Workato offre l'orchestration, la gouvernance et la confiance nécessaires dans l'entreprise. **Average Rating:** 4.7/5.0 **Total Reviews:** 748 #### How Do G2 Users Rate Workato? - **the product a-t-il été un bon partenaire commercial?:** 9.4/10 (Category avg: 8.9/10) - **Qualité du support:** 9.2/10 (Category avg: 8.9/10) - **Facilité d’utilisation:** 9.0/10 (Category avg: 8.9/10) - **Facilité d’administration:** 9.0/10 (Category avg: 8.5/10) #### Who Is the Company Behind Workato? - **Vendeur:** [Workato](https://www.g2.com/fr/sellers/workato) - **Site Web de l'entreprise:** www.workato.com - **Année de fondation:** 2013 - **Emplacement du siège social:** Mountain View, California - **Twitter:** @Workato 3,641 abonnés Twitter - **Page LinkedIn®:** [www.linkedin.com](https://www.g2.com/fr/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=229b7e77382a8d2c3a0aeebe68dfc2316ea2caa6dd5d95ed0ee0d08884e6fc88&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F3675685&secure%5Burl_type%5D=linkedin_company_website) 1,401 employés sur LinkedIn® #### Who Uses This Product? - **Who Uses This:** Ingénieur logiciel, Ingénieur Logiciel Senior - **Top Industries:** Logiciels informatiques, Technologie de l'information et services - **Company Size:** 43% Medium, 33% Large #### What Do G2 Reviewers Say About Workato? _AI-generated summary from verified user reviews_ ##### Pros - Les utilisateurs trouvent que Workato est **convivial et efficace** , permettant une automatisation facile sans expertise technique. - Les utilisateurs adorent les **intégrations faciles** offertes par Workato, rendant l'automatisation entre les outils simple et efficace. - Les utilisateurs apprécient la **facilité des intégrations** avec Workato, appréciant son interface conviviale et ses nombreux connecteurs préconstruits. - Les utilisateurs apprécient la **conception conviviale et les capacités d'automatisation** de Workato, qui améliorent la productivité et simplifient les flux de travail complexes. - Les utilisateurs adorent la **facilité d'automatisation** dans Workato, économisant des heures en intégrant sans effort divers outils et systèmes. ##### Cons - Les utilisateurs trouvent la **complexité** de Workato intimidante, surtout en ce qui concerne la terminologie et les structures tarifaires qui embrouillent les nouveaux venus. - Les utilisateurs trouvent la **, avec des flux de travail complexes et une intégration accablante compliquant l'utilisation initiale.** - Les utilisateurs expriment leur frustration face aux **limitations de données** dans Workato, ce qui entrave l'envoi d'e-mails et le transfert de fichiers pour des tâches plus importantes. - Les utilisateurs trouvent la **bibliothèque d'applications limitée** de Workato restrictive, nécessitant une configuration manuelle pour les intégrations moins courantes. - Les utilisateurs sont confrontés à une **courbe d'apprentissage abrupte** avec Workato, trouvant l'intégration et la configuration initiale assez accablantes et complexes. #### What Are Recent G2 Reviews of Workato? **["Workato nous aide à construire des intégrations complexes à une vitesse fulgurante."](https://www.g2.com/fr/survey_responses/workato-review-10305521)** **Rating:** 5.0/5.0 stars _— Sreenath B._ [Read full review](https://www.g2.com/fr/survey_responses/workato-review-10305521) **["La plateforme qui a grandi avec nous"](https://www.g2.com/fr/survey_responses/workato-review-12941177)** **Rating:** 5.0/5.0 stars _— Anshu b._ [Read full review](https://www.g2.com/fr/survey_responses/workato-review-12941177) #### What Are G2 Users Discussing About Workato? - [What does Workato do?](https://www.g2.com/fr/discussions/what-does-workato-do) - [Combien coûte Workato ?](https://www.g2.com/fr/discussions/how-much-does-workato-cost) - 1 comment - [Qu'est-ce qu'une recette Workato ?](https://www.g2.com/fr/discussions/what-is-a-workato-recipe) - 3 comments - [What is Workato used for?](https://www.g2.com/fr/discussions/what-is-workato-used-for) ### [Azure Data Factory](https://www.g2.com/fr/products/azure-data-factory/reviews) Azure Data Factory (ADF) est un service d'intégration de données entièrement géré et sans serveur, conçu pour simplifier le processus d'ingestion, de préparation et de transformation des données provenant de sources diverses. Il permet aux organisations de construire et d'orchestrer des flux de travail Extract, Transform, Load (ETL) et Extract, Load, Transform (ELT) dans un environnement sans code, facilitant le mouvement et la transformation des données entre les systèmes sur site et basés sur le cloud. Caractéristiques clés et fonctionnalités : - Connectivité étendue : ADF offre plus de 90 connecteurs intégrés, permettant l'intégration avec une large gamme de sources de données, y compris les bases de données relationnelles, les systèmes NoSQL, les applications SaaS, les API et les services de stockage cloud. - Transformation de données sans code : En utilisant des flux de données de mappage alimentés par Apache Spark™, ADF permet aux utilisateurs d'effectuer des transformations de données complexes sans écrire de code, simplifiant ainsi le processus de préparation des données. - Rehébergement de paquets SSIS : Les organisations peuvent facilement migrer et étendre leurs paquets SQL Server Integration Services (SSIS) existants vers le cloud, réalisant ainsi des économies significatives et une évolutivité accrue. - Évolutif et économique : En tant que service sans serveur, ADF s'adapte automatiquement pour répondre aux demandes d'intégration de données, offrant un modèle de tarification à l'utilisation qui élimine le besoin d'investissements initiaux en infrastructure. - Surveillance et gestion complètes : ADF fournit des outils de surveillance robustes, permettant aux utilisateurs de suivre la performance des pipelines, de configurer des alertes et d'assurer le fonctionnement efficace des flux de travail de données. Valeur principale et solutions pour les utilisateurs : Azure Data Factory répond aux complexités de l'intégration de données moderne en fournissant une plateforme unifiée qui connecte des sources de données disparates, automatise les flux de travail de données et facilite les transformations de données avancées. Cela permet aux organisations de tirer des insights exploitables de leurs données, d'améliorer les processus de prise de décision et d'accélérer les initiatives de transformation numérique. En offrant un environnement évolutif, économique et sans code, ADF réduit la charge opérationnelle des équipes informatiques et permet aux ingénieurs de données et aux analystes commerciaux de se concentrer sur la création de valeur grâce à des stratégies basées sur les données. **Average Rating:** 4.6/5.0 **Total Reviews:** 96 #### How Do G2 Users Rate Azure Data Factory? - **the product a-t-il été un bon partenaire commercial?:** 9.1/10 (Category avg: 8.9/10) - **Qualité du support:** 8.8/10 (Category avg: 8.9/10) - **Facilité d’utilisation:** 8.9/10 (Category avg: 8.9/10) - **Facilité d’administration:** 8.7/10 (Category avg: 8.5/10) #### Who Is the Company Behind Azure Data Factory? - **Vendeur:** [Microsoft](https://www.g2.com/fr/sellers/microsoft) - **Année de fondation:** 1975 - **Emplacement du siège social:** Redmond, Washington - **Twitter:** @microsoft 13,091,739 abonnés Twitter - **Page LinkedIn®:** [www.linkedin.com](https://www.g2.com/fr/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=9458f51bd6ded48ad432a804f19ad736469f007787569b63827154231c315630&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fmicrosoft%2F&secure%5Burl_type%5D=linkedin_company_website) 231,632 employés sur LinkedIn® - **Propriété:** MSFT #### Who Uses This Product? - **Who Uses This:** Ingénieur de données, Ingénieur logiciel - **Top Industries:** Technologie de l'information et services, Logiciels informatiques - **Company Size:** 59% Large, 31% Medium #### What Do G2 Reviewers Say About Azure Data Factory? _AI-generated summary from verified user reviews_ ##### Pros - Les utilisateurs adorent les **capacités d'intégration de données transparentes** d'Azure Data Factory, simplifiant les flux de travail complexes et améliorant la productivité. - Les utilisateurs apprécient la **facilité d'utilisation** d'Azure Data Factory, simplifiant l'intégration des données avec son interface visuelle à faible code. - Les utilisateurs apprécient la **connectivité transparente** d'Azure Data Factory pour intégrer diverses sources de données avec un minimum de codage. - Les utilisateurs apprécient les **capacités d'intégration transparentes** d'Azure Data Factory, simplifiant les flux de travail de données complexes à travers diverses sources. - Les utilisateurs apprécient la **scalabilité** d'Azure Data Factory, leur permettant de gérer et d'intégrer sans effort de vastes sources de données. ##### Cons - Les utilisateurs trouvent la **difficulté de débogage** dans Azure Data Factory frustrante, en particulier pour les pipelines complexes et le dépannage des échecs. - Les utilisateurs trouvent **difficile le débogage** avec Azure Data Factory, rencontrant souvent des défis pour résoudre efficacement les problèmes dans des pipelines complexes. - Les utilisateurs trouvent Azure Data Factory **cher** en raison des coûts imprévisibles liés aux exécutions de pipelines et aux mouvements de données. - Les utilisateurs trouvent que les **limitations des fonctionnalités** d'Azure Data Factory entravent leur capacité à surveiller et à s'intégrer efficacement avec Power BI. - Les utilisateurs trouvent que la **complexité et les limitations** d'Azure Data Factory sont difficiles, en particulier pour le débogage et la gestion de flux de travail complexes. #### What Are Recent G2 Reviews of Azure Data Factory? **["Intégration de données intuitive et évolutive avec Azure Data Factory"](https://www.g2.com/fr/survey_responses/azure-data-factory-review-12454264)** **Rating:** 4.5/5.0 stars _— Alan R._ [Read full review](https://www.g2.com/fr/survey_responses/azure-data-factory-review-12454264) **["Glisser-déposer à faible code qui facilite le développement pour les développeurs et les utilisateurs professionnels"](https://www.g2.com/fr/survey_responses/azure-data-factory-review-12746463)** **Rating:** 4.5/5.0 stars _— Shyam s._ [Read full review](https://www.g2.com/fr/survey_responses/azure-data-factory-review-12746463) #### What Are G2 Users Discussing About Azure Data Factory? - [Is Azure data Factory an ETL tool?](https://www.g2.com/fr/discussions/is-azure-data-factory-an-etl-tool) - 2 comments - [What are the additional capabilities of data Factory?](https://www.g2.com/fr/discussions/what-are-the-additional-capabilities-of-data-factory) - [Which 3 types of activities can you run in Microsoft Azure data Factory?](https://www.g2.com/fr/discussions/which-3-types-of-activities-can-you-run-in-microsoft-azure-data-factory) - [What does Azure data/factory do?](https://www.g2.com/fr/discussions/what-does-azure-data-factory-do) ### [SnapLogic Intelligent Integration Platform (IIP)](https://www.g2.com/fr/products/snaplogic-intelligent-integration-platform-iip/reviews) La plateforme SnapLogic est une solution d'intégration et d'automatisation agentique qui aide les équipes d'entreprise à connecter des applications, des sources de données et des API, et à orchestrer des flux de travail alimentés par l'IA à travers des environnements cloud et sur site. SnapLogic a son siège à San Mateo, en Californie. Fondée en 2006, l'entreprise sert des clients dans divers secteurs, notamment les services financiers, les produits pharmaceutiques, la fabrication, les logiciels et l'enseignement supérieur, avec des bureaux en Amérique du Nord, en Europe et en Asie-Pacifique. La plateforme est conçue pour les équipes informatiques, les ingénieurs de données et les spécialistes de l'intégration qui ont besoin de déplacer des données entre les systèmes, d'automatiser les processus métier et de gérer l'activité des agents IA à grande échelle. Elle prend en charge des cas d'utilisation tels que l'intégration d'applications, la gestion des pipelines de données, la gestion du cycle de vie des API, la modernisation des systèmes hérités et l'orchestration de l'IA d'entreprise. \*\*Les principales fonctionnalités et capacités de la plateforme SnapLogic incluent :\*\* - Constructeur de pipelines visuel et à faible code : Un concepteur par glisser-déposer qui permet aux équipes de créer, tester et déployer des intégrations sans écrire de code personnalisé, réduisant ainsi la dépendance aux ressources de développement. - Bibliothèque de connecteurs Snaps préconstruits : Plus de 1 000 connecteurs réutilisables pour les applications d'entreprise, les bases de données, les services cloud et les plateformes de données, configurables pour des modèles d'intégration simples et complexes. - SnapGPT : Un copilote IA intégré à la plateforme qui génère des pipelines d'intégration, suggère des mappages de données et aide au dépannage des pipelines en utilisant des entrées en langage naturel. - Gestion des API : Outils pour créer, publier, sécuriser et surveiller les API, permettant aux organisations d'exposer et de consommer des services de données à travers des systèmes internes et externes. - Automatisation des flux de travail agentique : Capacités pour concevoir et orchestrer des agents IA qui exécutent des processus métier en plusieurs étapes, avec un support natif pour le protocole de contexte de modèle (MCP) pour gérer les interactions des agents à travers les modèles et les outils. - Intégration et transformation des données : Support pour les pipelines de données par lots, en temps réel et en streaming avec des capacités de transformation, de mappage et d'enrichissement intégrées pour les données structurées et non structurées. - Surveillance et gouvernance centralisées : Un tableau de bord unifié pour suivre la performance des pipelines, gérer les contrôles d'accès et maintenir l'auditabilité de toutes les activités d'intégration et d'automatisation. La plateforme SnapLogic répond aux défis courants auxquels les organisations sont confrontées lorsqu'elles développent leurs opérations technologiques : données fragmentées à travers des systèmes déconnectés, coûts élevés de développement d'intégration et complexité du déploiement de l'IA dans des environnements réglementés ou critiques. En fournissant une plateforme unifiée pour l'intégration traditionnelle et l'automatisation agentique, elle réduit la dépendance aux connecteurs codés sur mesure et permet aux équipes de créer et de gérer des intégrations sans nécessiter une expertise approfondie en ingénierie logicielle. **Average Rating:** 4.4/5.0 **Total Reviews:** 379 #### How Do G2 Users Rate SnapLogic Intelligent Integration Platform (IIP)? - **the product a-t-il été un bon partenaire commercial?:** 8.8/10 (Category avg: 8.9/10) - **Qualité du support:** 8.3/10 (Category avg: 8.9/10) - **Facilité d’utilisation:** 8.9/10 (Category avg: 8.9/10) - **Facilité d’administration:** 8.6/10 (Category avg: 8.5/10) #### Who Is the Company Behind SnapLogic Intelligent Integration Platform (IIP)? - **Vendeur:** [SnapLogic](https://www.g2.com/fr/sellers/snaplogic) - **Site Web de l'entreprise:** www.snaplogic.com - **Année de fondation:** 2006 - **Emplacement du siège social:** San Mateo, CA - **Twitter:** @SnapLogic 7,348 abonnés Twitter - **Page LinkedIn®:** [www.linkedin.com](https://www.g2.com/fr/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=5261a75f1a744444604a852bca79d92e4b9b8336bca6cd31b6688370561a9346&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F210766%2F&secure%5Burl_type%5D=linkedin_company_website) 305 employés sur LinkedIn® #### Who Uses This Product? - **Who Uses This:** Ingénieur de données, Consultant - **Top Industries:** Technologie de l'information et services, Logiciels informatiques - **Company Size:** 47% Large, 36% Medium #### What Do G2 Reviewers Say About SnapLogic Intelligent Integration Platform (IIP)? _AI-generated summary from verified user reviews_ ##### Pros - Les utilisateurs apprécient la **facilité d'utilisation** de SnapLogic, permettant une intégration rapide et une configuration de pipeline simple. - Les utilisateurs apprécient les **intégrations faciles** de SnapLogic, bénéficiant d'une interface conviviale et de divers connecteurs. - Les utilisateurs apprécient les capacités d' **intégration transparente** de SnapLogic IIP, permettant des connexions efficaces entre divers systèmes. - Les utilisateurs apprécient l' **interface conviviale** de SnapLogic, simplifiant les tâches et améliorant la productivité globale. - Les utilisateurs adorent la **simplicité de l'automatisation** dans SnapLogic IIP, permettant un développement plus rapide et des processus d'intégration efficaces. ##### Cons - Les utilisateurs signalent des **problèmes de performance** avec SnapLogic, surtout sous des charges de travail lourdes et dans la fonctionnalité d'équilibrage de charge. - Les utilisateurs éprouvent **de mauvaises performances** sous des charges de travail lourdes, ce qui entraîne de la frustration avec le débogage et des intégrations complexes. - Les utilisateurs rencontrent des **difficultés techniques** , y compris des défis de débogage et des baisses de performance lors de charges de travail importantes. - Les utilisateurs trouvent que la **complexité de la compréhension des Snaps** et la traçabilité des erreurs sont assez difficiles dans SnapLogic IIP. - Les utilisateurs signalent **un mauvais rapport d'erreurs** et un manque de clarté dans le débogage, compliquant le processus de dépannage. #### What Are Recent G2 Reviews of SnapLogic Intelligent Integration Platform (IIP)? **["Intégrations rapides et évolutives avec le concepteur intuitif de glisser-déposer de SnapLogic"](https://www.g2.com/fr/survey_responses/snaplogic-intelligent-integration-platform-iip-review-13212820)** **Rating:** 5.0/5.0 stars _— Ramakrishna k._ [Read full review](https://www.g2.com/fr/survey_responses/snaplogic-intelligent-integration-platform-iip-review-13212820) **["Intégrations ultra-rapides—économisent beaucoup de maux de tête de codage !"](https://www.g2.com/fr/survey_responses/snaplogic-intelligent-integration-platform-iip-review-13191310)** **Rating:** 5.0/5.0 stars _— Pavan Simhadri D._ [Read full review](https://www.g2.com/fr/survey_responses/snaplogic-intelligent-integration-platform-iip-review-13191310) #### What Are G2 Users Discussing About SnapLogic Intelligent Integration Platform (IIP)? - [À quoi sert la plateforme d'intégration intelligente SnapLogic (IIP) ?](https://www.g2.com/fr/discussions/what-is-snaplogic-intelligent-integration-platform-iip-used-for) - 1 comment ### [AWS Lake Formation](https://www.g2.com/fr/products/aws-lake-formation/reviews) AWS Lake Formation est un service entièrement géré pour construire, gérer, sécuriser et partager des données dans des lacs de données en quelques jours. Vous pouvez centraliser la sécurité et la gouvernance, et permettre le partage de données à travers l'organisation. **Average Rating:** 4.4/5.0 **Total Reviews:** 33 #### How Do G2 Users Rate AWS Lake Formation? - **the product a-t-il été un bon partenaire commercial?:** 9.0/10 (Category avg: 8.9/10) - **Qualité du support:** 8.3/10 (Category avg: 8.9/10) - **Facilité d’utilisation:** 8.7/10 (Category avg: 8.9/10) - **Facilité d’administration:** 8.0/10 (Category avg: 8.5/10) #### Who Is the Company Behind AWS Lake Formation? - **Vendeur:** [Amazon Web Services (AWS)](https://www.g2.com/fr/sellers/amazon-web-services-aws-3e93cc28-2e9b-4961-b258-c6ce0feec7dd) - **Année de fondation:** 2006 - **Emplacement du siège social:** Seattle, WA - **Twitter:** @awscloud 2,232,483 abonnés Twitter - **Page LinkedIn®:** [www.linkedin.com](https://www.g2.com/fr/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=072881eee28a2afe24f8d1bda9f20e3e146b9fb4b214f216411ce2ed6898b31e&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Famazon-web-services%2F&secure%5Burl_type%5D=linkedin_company_website) 147,094 employés sur LinkedIn® - **Propriété:** NASDAQ: AMZN #### Who Uses This Product? - **Top Industries:** Technologie de l'information et services - **Company Size:** 47% Small, 37% Large #### What Are Recent G2 Reviews of AWS Lake Formation? **["Meilleur service de gestion de lac de données cloud"](https://www.g2.com/fr/survey_responses/aws-lake-formation-review-7819323)** **Rating:** 5.0/5.0 stars _— Ravi B._ [Read full review](https://www.g2.com/fr/survey_responses/aws-lake-formation-review-7819323) **["Simplifie la gouvernance, nécessite de l'expérience pour l'installation"](https://www.g2.com/fr/survey_responses/aws-lake-formation-review-12863344)** **Rating:** 4.0/5.0 stars _— Atharva P._ [Read full review](https://www.g2.com/fr/survey_responses/aws-lake-formation-review-12863344) #### What Are G2 Users Discussing About AWS Lake Formation? - [Is AWS Lake Formation free?](https://www.g2.com/fr/discussions/is-aws-lake-formation-free) - [How do I create AWS data lake?](https://www.g2.com/fr/discussions/how-do-i-create-aws-data-lake) - [How does Lake formation work?](https://www.g2.com/fr/discussions/how-does-lake-formation-work) - [What does AWS Lake formation do?](https://www.g2.com/fr/discussions/what-does-aws-lake-formation-do) ### [Maia](https://www.g2.com/fr/products/matillion-maia/reviews) Maia est une plateforme d'automatisation des données alimentée par des agents d'IA autonomes qui construisent, maintiennent et font évoluer les produits de données, éliminant ainsi le travail manuel des données. Maia permet aux CDAOs et aux équipes de données d'entreprise de fournir des produits de données à l'échelle des machines tout en maintenant la gouvernance. Sa plateforme intégrée combine des agents spécialisés dans l'équipe Maia, ancrés dans l'intelligence des données organisationnelles du moteur de contexte Maia et exécutés à travers les outils de données gouvernés de la fondation Maia. Des organisations comme EDF, St. James’ Place et Nature’s Touch utilisent Maia pour automatiser le travail des données à grande échelle, moderniser les plateformes et accélérer les feuilles de route de l'IA sans augmenter les effectifs. Voyez Maia par vous-même. **Average Rating:** 4.5/5.0 **Total Reviews:** 120 #### How Do G2 Users Rate Maia? - **the product a-t-il été un bon partenaire commercial?:** 8.4/10 (Category avg: 8.9/10) - **Qualité du support:** 8.6/10 (Category avg: 8.9/10) - **Facilité d’utilisation:** 9.0/10 (Category avg: 8.9/10) - **Facilité d’administration:** 8.3/10 (Category avg: 8.5/10) #### Who Is the Company Behind Maia? - **Vendeur:** [Matillion](https://www.g2.com/fr/sellers/matillion) - **Site Web de l'entreprise:** www.matillion.com - **Année de fondation:** 2011 - **Emplacement du siège social:** Salford, GB - **Twitter:** @matillion 7,362 abonnés Twitter - **Page LinkedIn®:** [www.linkedin.com](https://www.g2.com/fr/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=9b553fae1e51bb2b58491b1c1d561a15b7dd370d485b1ff7affe8e7cbd75e1cf&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F2360297%2F&secure%5Burl_type%5D=linkedin_company_website) 463 employés sur LinkedIn® #### Who Uses This Product? - **Who Uses This:** Ingénieur de données - **Top Industries:** Logiciels informatiques, Technologie de l'information et services - **Company Size:** 47% Medium, 31% Large #### What Do G2 Reviewers Say About Maia? _AI-generated summary from verified user reviews_ ##### Pros - Les utilisateurs trouvent la **facilité d'utilisation** de l'interface de Maia inestimable pour une configuration ETL fluide et une compréhension aisée. - Les utilisateurs apprécient l' **automatisation transparente** de Matillion, rendant les processus ETL sans effort et efficaces sur toutes les plateformes. - Les utilisateurs apprécient l' **interface utilisateur simple** de Matillion, ce qui rend la configuration facile et conviviale pour tout le monde. - Les utilisateurs adorent l' **interface intuitive et simple** de Matillion, ce qui la rend facile à configurer et à naviguer pour les débutants. - Les utilisateurs louent Maia pour son **efficacité ETL** , rendant les flux de travail complexes conviviaux et évolutifs pour tous les niveaux d'analystes. ##### Cons - Les utilisateurs rencontrent des **problèmes de performance au travail** en raison des limitations de l'interpréteur Jython et des flux de travail à un seul fil. - Les utilisateurs trouvent le **modèle de tarification coûteux** , surtout à mesure que le volume de données augmente, ce qui affecte l'abordabilité globale. - Les utilisateurs signalent des **problèmes de performance au travail** avec l'interpréteur Jython et des limitations du flux de travail à un seul fil affectant l'efficacité. - Les utilisateurs expriment leur inquiétude concernant la **dépendance au cloud** , se sentant enfermés dans l'environnement avec des options de personnalisation limitées. - Les utilisateurs trouvent les **limitations de l'API** dans Maia frustrantes, car les fonctionnalités administratives manquent d'options d'accès et d'utilisabilité suffisantes. #### What Are Recent G2 Reviews of Maia? **["Maia rend l'intégration rapide avec une interface utilisateur intuitive et des pipelines à faible code"](https://www.g2.com/fr/survey_responses/maia-review-12942268)** **Rating:** 4.5/5.0 stars _— Anthony S._ [Read full review](https://www.g2.com/fr/survey_responses/maia-review-12942268) **["Maia a migré plus de 800 pipelines sans frais supplémentaires"](https://www.g2.com/fr/survey_responses/maia-review-12920298)** **Rating:** 5.0/5.0 stars _— Keith G._ [Read full review](https://www.g2.com/fr/survey_responses/maia-review-12920298) #### What Are G2 Users Discussing About Maia? - [À quoi sert Matillion ETL ?](https://www.g2.com/fr/discussions/what-is-matillion-etl-used-for) - 1 comment - [À quoi sert Matillion Data Loader ?](https://www.g2.com/fr/discussions/what-is-matillion-data-loader-used-for) - [What are ETL tools used for?](https://www.g2.com/fr/discussions/what-are-etl-tools-used-for) - [Is Matillion open source?](https://www.g2.com/fr/discussions/is-matillion-open-source) - [What is ETL in software?](https://www.g2.com/fr/discussions/what-is-etl-in-software) ### [Amazon Redshift](https://www.g2.com/products/amazon-redshift/reviews) Tens of thousands of customers use Amazon Redshift, a fast, fully managed, petabyte-scale data warehouse service that makes it simple and cost-effective to efficiently analyze all your data using your existing business intelligence tools. It is optimized for datasets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions. **Average Rating:** 4.3/5.0 **Total Reviews:** 371 #### How Do G2 Users Rate Amazon Redshift? - **Has the product been a good partner in doing business?:** 8.7/10 (Category avg: 8.9/10) - **Quality of Support:** 8.5/10 (Category avg: 8.9/10) - **Ease of Use:** 8.7/10 (Category avg: 8.9/10) - **Ease of Admin:** 8.4/10 (Category avg: 8.5/10) #### Who Is the Company Behind Amazon Redshift? - **Seller:** [Amazon Web Services (AWS)](https://www.g2.com/sellers/amazon-web-services-aws-3e93cc28-2e9b-4961-b258-c6ce0feec7dd) - **Year Founded:** 2006 - **HQ Location:** Seattle, WA - **Twitter:** @awscloud 2,232,483 Twitter followers - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=072881eee28a2afe24f8d1bda9f20e3e146b9fb4b214f216411ce2ed6898b31e&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Famazon-web-services%2F&secure%5Burl_type%5D=linkedin_company_website) 147,094 employees on LinkedIn® - **Ownership:** NASDAQ: AMZN #### Who Uses This Product? - **Who Uses This:** Data Engineer, Senior Data Engineer - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 40% Large, 39% Medium #### What Do G2 Reviewers Say About Amazon Redshift? _AI-generated summary from verified user reviews_ ##### Pros - Users value the **fast querying capabilities** of Amazon Redshift, enabling efficient analysis of large datasets seamlessly. - Users praise the **easy integrations** with other software, enhancing data solutions within the Amazon Redshift ecosystem. - Users find Amazon Redshift's **ease of use** exceptional, facilitating quick access and efficient data management. - Users value the **easy integrations** of Amazon Redshift, enhancing their ability to build seamless data solutions. - Users praise the **impressive speed and scalability** of Amazon Redshift, optimizing data management and query performance. ##### Cons - Users find **feature limitations** in Redshift, especially regarding advanced analytics and multi-language support for coding. - Users note significant **software limitations** with Redshift, particularly regarding cost and performance issues with complex queries. - Users find the **complexity of optimizations** in Amazon Redshift burdensome, requiring significant management and maintenance effort. - Users face **query issues** with Amazon Redshift, requiring extensive optimization and management to maintain performance. - Users find the **query optimization process cumbersome** , as it requires significant effort and specialized knowledge for efficiency. #### What Are Recent G2 Reviews of Amazon Redshift? **["Scalable and Efficient Cloud Data Platform"](https://www.g2.com/survey_responses/amazon-redshift-review-12872150)** **Rating:** 4.5/5.0 stars _— Swaroop W._ [Read full review](https://www.g2.com/survey_responses/amazon-redshift-review-12872150) **["Powerful Analytics Tool with Some Flexibility Limitations"](https://www.g2.com/survey_responses/amazon-redshift-review-12781722)** **Rating:** 4.0/5.0 stars _— Atharva P._ [Read full review](https://www.g2.com/survey_responses/amazon-redshift-review-12781722) #### What Are G2 Users Discussing About Amazon Redshift? - [What is Amazon Redshift used for?](https://www.g2.com/discussions/what-is-amazon-redshift-used-for) - [Is AWS redshift a database?](https://www.g2.com/discussions/is-aws-redshift-a-database) - 1 comment - [When can I use Amazon redshift?](https://www.g2.com/discussions/when-can-i-use-amazon-redshift) - 3 comments - [What are the characteristics of redshift?](https://www.g2.com/discussions/what-are-the-characteristics-of-redshift) - 2 comments - [What does Amazon redshift do?](https://www.g2.com/discussions/what-does-amazon-redshift-do) - 2 comments ### [5X](https://www.g2.com/fr/products/5x/reviews) 5X est une plateforme de données et d'IA de bout en bout. La plateforme organise vos données, quelle que soit leur source ou leur format. Que vous ayez ou non une équipe dédiée aux données, notre plateforme transforme les données fragmentées en informations exploitables et en applications. Le retour client que nous recevons le plus souvent est : « C'est explicite » et « C'est super facile à utiliser ». Et c'était exactement notre objectif : créer une plateforme puissante, tout-en-un, incroyablement facile à utiliser. La pile de données moderne a évolué. Il ne s'agit plus de rassembler des fournisseurs. La prochaine génération de la pile de données moderne est une plateforme tout-en-un qui offre rapidité, simplicité et réduction du coût de possession. C'est exactement ce que nous avons créé chez 5X. Les entreprises utilisent 5X pour plusieurs raisons : 1) Vitesse et productivité. Les plateformes de données tout-en-un sont incroyablement efficaces. Nous avons vu des entreprises créer des cas d'utilisation dès le premier jour. Contactez-nous pour voir si vous êtes éligible pour un démarrage gratuit de 48 heures ! 🚀 2) Réduisez votre coût total de possession de 30 % par rapport à la construction de votre propre plateforme. Cela ne prend pas en compte les heures de travail nécessaires pour soutenir la construction d'une plateforme 🤯 3) Utilisez notre service de conseil en données complet pour un soutien en ingénierie des données et en analytique 👨‍💻 5X a été fondée en 2020 avec une présence aux États-Unis, à Singapour, au Royaume-Uni et en Inde. Notre équipe mondiale compte plus de 70 personnes et croît rapidement. Nous avons récemment levé notre tour de financement initial auprès de Flybridge Capital et sommes soutenus par des fondateurs de premier plan d'entreprises comme Datadog, Preset, Astronomer, Mode, Rudderstack et d'autres investisseurs providentiels de renom. Pour plus d'informations, visitez 5X.co Nous ne parlons pas seulement de rapidité et de simplicité ; nous le prouvons. Parlez-nous de notre démarrage de 48 heures où nous pouvons construire un cas d'utilisation de bout en bout pour vous en 48 heures gratuitement. **Average Rating:** 4.9/5.0 **Total Reviews:** 81 #### How Do G2 Users Rate 5X? - **the product a-t-il été un bon partenaire commercial?:** 9.8/10 (Category avg: 8.9/10) - **Qualité du support:** 9.8/10 (Category avg: 8.9/10) - **Facilité d’utilisation:** 9.5/10 (Category avg: 8.9/10) - **Facilité d’administration:** 9.6/10 (Category avg: 8.5/10) #### Who Is the Company Behind 5X? - **Vendeur:** [5X](https://www.g2.com/fr/sellers/5x) - **Année de fondation:** 2020 - **Emplacement du siège social:** San Francisco - **Twitter:** @DataWith5x 49 abonnés Twitter - **Page LinkedIn®:** [www.linkedin.com](https://www.g2.com/fr/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=123d4698fdf0b6036b49dc7dd7e99f12fd6c91a432ee93cdc153ec13a4d274d7&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fdatawith5x%2F&secure%5Burl_type%5D=linkedin_company_website) 111 employés sur LinkedIn® #### Who Uses This Product? - **Top Industries:** Logiciels informatiques, Services financiers - **Company Size:** 56% Medium, 40% Small #### What Do G2 Reviewers Say About 5X? _AI-generated summary from verified user reviews_ ##### Pros - Les utilisateurs apprécient la **facilité d'utilisation** de 5X, appréciant son interface intuitive et son intégration transparente avec les outils existants. - Les utilisateurs apprécient le **support client réactif** de 5X, qui répond rapidement aux demandes et implémente les fonctionnalités demandées. - Les utilisateurs louent 5X pour ses **capacités d'intégration transparentes** , améliorant l'automatisation des flux de travail et simplifiant la gestion des données à travers les plateformes. - Les utilisateurs apprécient les **intégrations faciles** de 5X, améliorant leur ingestion de données et leur efficacité opérationnelle globale sans effort. - Les utilisateurs louent 5X pour son **design intuitif et ses capacités intégrées** , facilitant une gestion efficace des données et des flux de travail sans heurts. ##### Cons - Les utilisateurs trouvent une **courbe d'apprentissage abrupte** avec 5X au début, mais la formation aide à faciliter la transition. - Les utilisateurs trouvent la **configuration complexe** de 5X difficile, nécessitant souvent un support supplémentaire pour un déploiement réussi. - Les utilisateurs trouvent une **courbe d'apprentissage abrupte** au début, nécessitant des sessions de formation pour s'adapter à la complexité de la plateforme. - Les utilisateurs trouvent que la **configuration difficile** du 5X est chronophage, nécessitant un apprentissage approfondi et un support pour des intégrations complexes. - Les utilisateurs notent les **limitations des fonctionnalités** car certains outils avancés sont encore en développement, affectant la fonctionnalité globale et les flux de travail. #### What Are Recent G2 Reviews of 5X? **["Un partenaire de données fiable et évolutif"](https://www.g2.com/fr/survey_responses/5x-review-11889175)** **Rating:** 5.0/5.0 stars _— Varinderjit K._ [Read full review](https://www.g2.com/fr/survey_responses/5x-review-11889175) **["Soutien exceptionnel et plateforme conviviale propulsant notre transformation des données"](https://www.g2.com/fr/survey_responses/5x-review-11903408)** **Rating:** 4.0/5.0 stars _— Shuming F._ [Read full review](https://www.g2.com/fr/survey_responses/5x-review-11903408) ### [Astro by Astronomer](https://www.g2.com/fr/products/astro-by-astronomer/reviews) Pour les équipes de données cherchant à augmenter la disponibilité des données fiables, Astronomer propose Astro, la plateforme moderne d'orchestration de données, propulsée par Airflow. Astro permet aux ingénieurs de données, aux scientifiques de données et aux analystes de données de construire, exécuter et observer des pipelines en tant que code. Astronomer est la force motrice derrière Apache Airflow™, la norme de facto pour exprimer les flux de données en tant que code. Airflow est téléchargé plus de 31 millions de fois chaque mois et est utilisé par des centaines de milliers d'équipes à travers le monde. **Average Rating:** 4.5/5.0 **Total Reviews:** 135 #### How Do G2 Users Rate Astro by Astronomer? - **the product a-t-il été un bon partenaire commercial?:** 9.0/10 (Category avg: 8.9/10) - **Qualité du support:** 8.9/10 (Category avg: 8.9/10) - **Facilité d’utilisation:** 9.0/10 (Category avg: 8.9/10) - **Facilité d’administration:** 8.8/10 (Category avg: 8.5/10) #### Who Is the Company Behind Astro by Astronomer? - **Vendeur:** [Astronomer](https://www.g2.com/fr/sellers/astronomer) - **Site Web de l'entreprise:** www.astronomer.io - **Année de fondation:** 2018 - **Emplacement du siège social:** New York, US - **Twitter:** @astronomerio 19,697 abonnés Twitter - **Page LinkedIn®:** [www.linkedin.com](https://www.g2.com/fr/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=14de7865093cbe981bc53aa7236a5a16a9a7e76fb4d0a5b96f23ea594dfac03b&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F10019299&secure%5Burl_type%5D=linkedin_company_website) 4,562 employés sur LinkedIn® #### Who Uses This Product? - **Who Uses This:** Ingénieur de données, Ingénieur de données senior - **Top Industries:** Technologie de l'information et services, Services financiers - **Company Size:** 47% Medium, 38% Large #### What Do G2 Reviewers Say About Astro by Astronomer? _AI-generated summary from verified user reviews_ ##### Pros - Les utilisateurs soulignent la **facilité d'utilisation** d'Astro, avec une interface utilisateur intuitive et une intégration transparente avec Slack pour la surveillance. - Les utilisateurs apprécient l' **amélioration de l'efficacité** d'Astro, qui améliore la gestion du flux de travail et économise un temps précieux. - Les utilisateurs apprécient l' **interface utilisateur intuitive** d'Astro, simplifiant les flux de travail complexes et améliorant la collaboration en équipe. - Les utilisateurs adorent les **capacités d'automatisation** d'Astro par Astronomer, améliorant l'efficacité dans l'orchestration et la surveillance des données. - Les utilisateurs apprécient la **facilité de déploiement** d'Astro par Astronomer, qui simplifie Airflow et assure une gestion fiable des pipelines de données. ##### Cons - Les utilisateurs expriment des préoccupations concernant Astro par Astronomer en raison de ses **prix élevés** et de son manque de transparence, en particulier pour les petites équipes. - Les utilisateurs signalent une **courbe d'apprentissage abrupte** pour les nouveaux membres de l'équipe, nécessitant un temps considérable pour l'adaptation et la formation. - Les utilisateurs ont du mal avec une **courbe d'apprentissage abrupte** , rendant l'adaptation et la formation pour Astro difficiles pour les nouveaux membres de l'équipe. - Les utilisateurs trouvent souvent une **courbe d'apprentissage abrupte** avec Astro, nécessitant un temps supplémentaire pour l'adaptation et la formation des nouveaux utilisateurs. - Les utilisateurs trouvent la **personnalisation limitée** d'Astro restrictive, surtout par rapport aux options Airflow auto-hébergées. #### What Are Recent G2 Reviews of Astro by Astronomer? **["Excellente expérience pour les développeurs et les clients"](https://www.g2.com/fr/survey_responses/astro-by-astronomer-review-8428848)** **Rating:** 5.0/5.0 stars _— Juan Roberto H._ [Read full review](https://www.g2.com/fr/survey_responses/astro-by-astronomer-review-8428848) **["Asro aide littéralement dans le travail d'ingénierie des données, le rendant plus facile et plus productif."](https://www.g2.com/fr/survey_responses/astro-by-astronomer-review-8519803)** **Rating:** 5.0/5.0 stars _— Lakshminarayanan K._ [Read full review](https://www.g2.com/fr/survey_responses/astro-by-astronomer-review-8519803) #### What Are G2 Users Discussing About Astro by Astronomer? - [What is your experience with Astro by Astronomer for data orchestration, and what challenges have you faced?](https://www.g2.com/fr/discussions/what-is-your-experience-with-astro-by-astronomer-for-data-orchestration-and-what-challenges-have-you-faced) - [À quoi sert Astro par Astronomer ?](https://www.g2.com/fr/discussions/what-is-astro-by-astronomer-used-for) ### [IBM webMethods B2B](https://www.g2.com/products/ibm-webmethods-b2b/reviews) Simplify the complexity of how you B2B with IBM webMethods B2B. The B2B integration allows you to share documents—purchase orders, invoices, shipping notices, contracts and more—in the cloud and keep everything in sync with APIs. **Average Rating:** 4.5/5.0 **Total Reviews:** 56 #### How Do G2 Users Rate IBM webMethods B2B? - **Has the product been a good partner in doing business?:** 8.4/10 (Category avg: 8.9/10) - **Quality of Support:** 8.7/10 (Category avg: 8.9/10) - **Ease of Use:** 8.9/10 (Category avg: 8.9/10) - **Ease of Admin:** 8.2/10 (Category avg: 8.5/10) #### Who Is the Company Behind IBM webMethods B2B? - **Seller:** [IBM](https://www.g2.com/sellers/ibm) - **Year Founded:** 1911 - **HQ Location:** Armonk, New York, United States - **Twitter:** @IBMSecurity 74,660 Twitter followers - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=14b544adaece4fdbc987f1d7f7028048c22259946811200cc751263825586af9&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F1009%2F&secure%5Burl_type%5D=linkedin_company_website) 328,202 employees on LinkedIn® - **Ownership:** SWX:IBM #### Who Uses This Product? - **Top Industries:** Staffing and Recruiting, Computer Software - **Company Size:** 42% Medium, 35% Large #### What Do G2 Reviewers Say About IBM webMethods B2B? _AI-generated summary from verified user reviews_ ##### Pros - Users appreciate the **ease of use** in IBM webMethods B2B, simplifying communication and process management with trade partners. - Users value the **seamless data exchange** and robust features that simplify B2B integration and automation. - Users highly value the **strong security features** of IBM webMethods B2B, ensuring safe and reliable transactions. - Users value the **end-to-end automation** of B2B processes, enhancing efficiency and simplifying data exchange with partners. - Users value the **integration capabilities** of IBM webMethods B2B, facilitating seamless connections and document exchanges with partners. ##### Cons - Users find the **complexity** of IBM webMethods B2B to be challenging, impacting user experience and customization options. - Users find the pricing structure of IBM webMethods B2B to be **expensive** and challenging for smaller businesses. - Users find the **difficult learning curve** of IBM webMethods B2B to be challenging, especially for newcomers to B2B integrations. - Users express concerns over the **complex pricing structure** of webMethods B2B, finding it challenging to fit budgets. - Users may experience a **learning curve** with webMethods.io B2B, especially those new to integration tools. #### What Are Recent G2 Reviews of IBM webMethods B2B? **["Efficient tool for business document processing over cloud infrastructure"](https://www.g2.com/survey_responses/ibm-webmethods-b2b-review-9536771)** **Rating:** 4.0/5.0 stars _— Mahesh B._ [Read full review](https://www.g2.com/survey_responses/ibm-webmethods-b2b-review-9536771) **["Strongly recommend to use"](https://www.g2.com/survey_responses/ibm-webmethods-b2b-review-10173432)** **Rating:** 5.0/5.0 stars _— Shilpa J._ [Read full review](https://www.g2.com/survey_responses/ibm-webmethods-b2b-review-10173432) ### [Azure Synapse Analytics](https://www.g2.com/products/azure-synapse-analytics/reviews) Azure Synapse Analytics is a cloud-based Enterprise Data Warehouse (EDW) that leverages Massively Parallel Processing (MPP) to quickly run complex queries across petabytes of data. **Average Rating:** 4.4/5.0 **Total Reviews:** 37 #### How Do G2 Users Rate Azure Synapse Analytics? - **Has the product been a good partner in doing business?:** 8.3/10 (Category avg: 8.9/10) - **Quality of Support:** 8.7/10 (Category avg: 8.9/10) - **Ease of Use:** 8.8/10 (Category avg: 8.9/10) - **Ease of Admin:** 8.9/10 (Category avg: 8.5/10) #### Who Is the Company Behind Azure Synapse Analytics? - **Seller:** [Microsoft](https://www.g2.com/sellers/microsoft) - **Year Founded:** 1975 - **HQ Location:** Redmond, Washington - **Twitter:** @microsoft 13,091,739 Twitter followers - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=9458f51bd6ded48ad432a804f19ad736469f007787569b63827154231c315630&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fmicrosoft%2F&secure%5Burl_type%5D=linkedin_company_website) 231,632 employees on LinkedIn® - **Ownership:** MSFT #### Who Uses This Product? - **Top Industries:** Information Technology and Services - **Company Size:** 45% Medium, 32% Large #### What Do G2 Reviewers Say About Azure Synapse Analytics? _AI-generated summary from verified user reviews_ ##### Pros - Users laud the **unified analytics experience** of Azure Synapse Analytics, enhancing efficiency and simplifying complex data processes. - Users value the **automation capabilities** of Azure Synapse Analytics, enhancing efficiency in data analytics solutions. - Users appreciate the **seamless cloud integration** of Azure Synapse Analytics, enhancing data workflows and overall efficiency. - Users value the **cost-effective** capabilities of Azure Synapse Analytics, enjoying scalable solutions without high expenditures. - Users appreciate the **seamless data integration** capabilities of Azure Synapse Analytics, enhancing efficiency and simplifying analytics solutions. ##### Cons - Users find the **cost estimation process complex** due to difficulties in monitoring and optimizing various service components. - Users face challenges with **cost management** , struggling with optimization and monitoring across various Azure Synapse components. - Users face challenges with **debugging complex pipeline failures** due to a lack of detailed error transparency, increasing troubleshooting time. - Users face **difficult debugging** due to a steep learning curve and lack of detailed error transparency during pipeline failures. - Users find Azure Synapse Analytics **expensive** , especially when managing costs across multiple services and queries. #### What Are Recent G2 Reviews of Azure Synapse Analytics? **["Unified Data Warehousing and Big Data in One Powerful Platform"](https://www.g2.com/survey_responses/azure-synapse-analytics-review-12435130)** **Rating:** 4.5/5.0 stars _— Daniel H._ [Read full review](https://www.g2.com/survey_responses/azure-synapse-analytics-review-12435130) **["Unified Analytics Platform with Seamless Azure Integration"](https://www.g2.com/survey_responses/azure-synapse-analytics-review-12353239)** **Rating:** 4.0/5.0 stars _— Ashish D._ [Read full review](https://www.g2.com/survey_responses/azure-synapse-analytics-review-12353239) #### What Are G2 Users Discussing About Azure Synapse Analytics? - [Does Azure Synapse include Analysis Services?](https://www.g2.com/discussions/does-azure-synapse-include-analysis-services) - [When should use Azure synapse analytics?](https://www.g2.com/discussions/when-should-use-azure-synapse-analytics) - [What are advantages of Azure synapse analytics?](https://www.g2.com/discussions/what-are-advantages-of-azure-synapse-analytics) - [What is included in Azure synapse analytics?](https://www.g2.com/discussions/what-is-included-in-azure-synapse-analytics) ### [dbt](https://www.g2.com/products/dbt/reviews) dbt is a transformation workflow that lets data teams quickly and collaboratively deploy analytics code following software engineering best practices like modularity, portability, CI/CD, and documentation. Now anyone who knows SQL can build production-grade data pipelines. **Average Rating:** 4.7/5.0 **Total Reviews:** 208 #### How Do G2 Users Rate dbt? - **Has the product been a good partner in doing business?:** 8.6/10 (Category avg: 8.9/10) - **Quality of Support:** 8.8/10 (Category avg: 8.9/10) - **Ease of Use:** 9.0/10 (Category avg: 8.9/10) - **Ease of Admin:** 8.5/10 (Category avg: 8.5/10) #### Who Is the Company Behind dbt? - **Seller:** [Fivetran](https://www.g2.com/sellers/fivetran) - **Year Founded:** 2012 - **HQ Location:** Oakland, CA - **Twitter:** @fivetran 5,767 Twitter followers - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=7f1ca0a984cd3b7fe678e6cf023235ee7978629644faf3910a5df7f92b63eea3&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Ffivetran%2F&secure%5Burl_type%5D=linkedin_company_website) 1,848 employees on LinkedIn® #### Who Uses This Product? - **Who Uses This:** Data Engineer, Analytics Engineer - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 56% Medium, 27% Small #### What Do G2 Reviewers Say About dbt? _AI-generated summary from verified user reviews_ ##### Pros - Users love the **ease of use** of dbt, thanks to its clear structure, intuitive documentation, and seamless integration. - Users value dbt for its **integration of software engineering best practices** , enhancing maintainability and collaboration in SQL transformations. - Users value the **automation** features of dbt, significantly enhancing SQL code maintainability and transforming data workflows. - Users value the **transformative power** of dbt, efficiently organizing and modeling data for actionable insights. - Users value dbt for its **high data quality** , ensuring integrity and enhancing analytics workflows through modularization and documentation. ##### Cons - Users face challenges with **limited functionality** in dbt due to rigid models and debugging difficulties, affecting project progress. - Users often face **dependency issues** with dbt, leading to time-consuming troubleshooting and disruption in workflows. - Users find the **steep learning curve** of mastering concepts like Jinja and Git to be quite challenging. - Users struggle with **unhelpful error messages** in dbt, making troubleshooting difficult and frustrating. - Users face **confusing error reporting** that complicates troubleshooting and hinders quick identification of issues. #### What Are Recent G2 Reviews of dbt? **["Simple SQL-Driven Materializations with Powerful Lineage"](https://www.g2.com/survey_responses/dbt-review-12985641)** **Rating:** 5.0/5.0 stars _— Anish G._ [Read full review](https://www.g2.com/survey_responses/dbt-review-12985641) **["dbt Streamlines Data Pipelines with Powerful Incremental and SCD2 Features"](https://www.g2.com/survey_responses/dbt-review-12712114)** **Rating:** 5.0/5.0 stars _— Hithesh P._ [Read full review](https://www.g2.com/survey_responses/dbt-review-12712114) #### What Are G2 Users Discussing About dbt? - [What is DBT data Modelling?](https://www.g2.com/discussions/what-is-dbt-data-modelling) - 2 comments - [What is DBT technology?](https://www.g2.com/discussions/what-is-dbt-technology) - 2 comments - [What is DBT database tool?](https://www.g2.com/discussions/what-is-dbt-database-tool) - 1 comment - [What is DBT tool used for?](https://www.g2.com/discussions/what-is-dbt-tool-used-for) - 2 comments - ‹ Prev ‹ Prev - 1 - [2](/categories/big-data-integration-platforms?order=g2_score&page=2#product-list) - [3](/categories/big-data-integration-platforms?order=g2_score&page=3#product-list) - [4](/categories/big-data-integration-platforms?order=g2_score&page=4#product-list) - [5](/categories/big-data-integration-platforms?order=g2_score&page=5#product-list) - … - [8](/categories/big-data-integration-platforms?order=g2_score&page=8#product-list) - [9](/categories/big-data-integration-platforms?order=g2_score&page=9#product-list) - [Next › Next ›](/categories/big-data-integration-platforms?order=g2_score&page=2#product-list) Spotlight Categories [Social Media Management Tools](https://www.g2.com/categories/social-media-mgmt) [Mobile Device Management (MDM) Software](https://www.g2.com/categories/mobile-device-management-mdm) [Performance Management Software](https://www.g2.com/categories/performance-management) [Outbound Call Tracking Software](https://www.g2.com/categories/outbound-call-tracking) [Chatbots Software](https://www.g2.com/categories/chatbots) Similar Categories - [Cloud Migration](/categories/cloud-migration) - [Embedded Integration Platforms](/categories/embedded-integration-platforms) - [Enterprise Service Bus (ESB)](/categories/enterprise-service-bus-esb) - [ETL Tools](/categories/etl-tools) - [iPaaS](/categories/ipaas) - [Reverse ETL](/categories/reverse-etl) - [Stream Analytics](/categories/stream-analytics) [Browse Big Data Integration Platforms Themes](/categories/big-data-integration-platforms/themes) ![Shalaka Joshi](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Shalaka Joshi") SJ Researched and written by [Shalaka Joshi](https://research.g2.com/insights/author/shalaka-joshi) Updated April 9, 2026 Big data integration platforms facilitate the integration and analysis of large-scale data across cloud applications and databases, helping companies manage and utilize enormous volumes of data collected from IoT endpoints, applications, and communications by creating structured pipelines that connect big data processing outputs to downstream systems. ### Core Capabilities of Big Data Integration Platforms To qualify for inclusion in the Big Data Integration category, a product must: - Integrate big data processing data to external sources - Ingest and distribute large sets of homogenous and heterogeneous data - Create a structured pipeline for big data management processes ### Common Use Cases for Big Data Integration Platforms Data engineering and IT teams use big data integration platforms to connect large-scale data environments with business applications and analytics systems. Common use cases include: - Integrating processed big data clusters with cloud applications and databases for downstream use - Simplifying the management of high-volume IoT and application data across distributed environments - Building structured data pipelines that enable consistent, reliable access to big data insights across the organization ### How Big Data Integration Platforms Differ from Other Tools Big data integration platforms typically require big data to have been processed prior to integration, working in conjunction with [big data processing and distribution software](https://www.g2.com/categories/big-data-processing-and-distribution) rather than replacing it. While some platforms provide [stream analytics](https://www.g2.com/categories/stream-analytics) capabilities, their primary focus is on data management and integration pipelines rather than real-time analytical processing. ### Insights from G2 on Big Data Integration Platforms Based on category trends on G2, pipeline flexibility and broad connector support for cloud applications and databases as standout capabilities. Improved data accessibility across systems and reduced integration complexity stand out as primary outcomes of adoption. Top Tools at a Glance | Product | Best for | User Review | | --- | --- | --- | | [![Product Avatar Image](https://images.g2crowd.com/uploads/product/image/large_detail/large_detail_96b275379465d759df5bffd0099d849a/google-cloud-bigquery.png "Product Avatar Image")](https://www.g2.com/products/google-cloud-bigquery/reviews)[BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews)[4.5/5(1,224)](https://www.g2.com/products/google-cloud-bigquery/reviews) | Serverless SQL analytics across Google-native data pipelines | "Easy-to-Use Cloud Tool with Shareable, Saved Queries" | | [![Product Avatar Image](https://images.g2crowd.com/uploads/product/image/large_detail/large_detail_2c6c77d8284b2f6609c2f9dc0ba6b5a9/alteryx.png "Product Avatar Image")](https://www.g2.com/products/alteryx/reviews)[Alteryx](https://www.g2.com/products/alteryx/reviews)[4.6/5(894)](https://www.g2.com/products/alteryx/reviews) | No-code ETL and multi-source data blending | "Makes Data Prep Faster with an Intuitive Drag-and-Drop Workflow" | | [![Product Avatar Image](https://images.g2crowd.com/uploads/product/image/large_detail/large_detail_2b00e05c107c3273cea5264090c3c1d0/snowflake.jpg "Product Avatar Image")](https://www.g2.com/products/snowflake/reviews)[Snowflake](https://www.g2.com/products/snowflake/reviews)[4.5/5(763)](https://www.g2.com/products/snowflake/reviews) | Multi-workload analytics with compute-storage separation | "Elastic Scaling and Fast Analytics with Snowflake" | | [![Product Avatar Image](https://images.g2crowd.com/uploads/product/image/large_detail/large_detail_50b25c72253e48a2b66e69f996196956/workato.png "Product Avatar Image")](https://www.g2.com/products/workato/reviews)[Workato](https://www.g2.com/products/workato/reviews)[4.7/5(777)](https://www.g2.com/products/workato/reviews) | Cross-application data orchestration with low-code recipes | "Workato helps us building complex integrations at lightning speed." | | [![Product Avatar Image](https://images.g2crowd.com/uploads/product/image/large_detail/large_detail_f176b4154a751d10150daa67a57b7dc5/azure-data-factory.jpg "Product Avatar Image")](https://www.g2.com/products/azure-data-factory/reviews)[Azure Data Factory](https://www.g2.com/products/azure-data-factory/reviews)[4.6/5(101)](https://www.g2.com/products/azure-data-factory/reviews) | Azure-native ETL orchestration across hybrid data sources | "Intuitive, Scalable Data Integration with Azure Data Factory" | | [![Product Avatar Image](https://images.g2crowd.com/uploads/product/image/large_detail/large_detail_c476c9375398c3b68bbf5ff649015bba/snaplogic-intelligent-integration-platform-iip.png "Product Avatar Image")](https://www.g2.com/products/snaplogic-intelligent-integration-platform-iip/reviews)[SnapLogic](https://www.g2.com/products/snaplogic-intelligent-integration-platform-iip/reviews)[4.4/5(406)](https://www.g2.com/products/snaplogic-intelligent-integration-platform-iip/reviews) | Low-code ETL pipeline building across hybrid environments | "Fast, Scalable Integrations with SnapLogic’s Intuitive Drag-and-Drop Designer" | | [![Product Avatar Image](https://images.g2crowd.com/uploads/product/image/large_detail/large_detail_b3390b4cc3d92e87d570895f7358c003/amazon-redshift.jpg "Product Avatar Image")](https://www.g2.com/products/amazon-redshift/reviews)[Amazon Redshift](https://www.g2.com/products/amazon-redshift/reviews)[4.3/5(404)](https://www.g2.com/products/amazon-redshift/reviews) | AWS-native analytical data warehousing at petabyte scale | "Powerful Analytics Tool with Some Flexibility Limitations" | * * * Show More ### Big Data Integration Platforms Topics - [What are Big Data Integration Platforms?](#what-are-big-data-integration-platforms) - [What are the Common Features of Big Data Integration Platforms?](#what-are-the-common-features-of-big-data-integration-platforms) - [What are the Benefits of Big Data Integration Platforms?](#what-are-the-benefits-of-big-data-integration-platforms) - [Who Uses Big Data Integration Platforms?](#who-uses-big-data-integration-platforms) - [Challenges with Big Data Integration Platforms](#challenges-with-big-data-integration-platforms) - [Which Companies Should Buy Big Data Integration Platforms?](#which-companies-should-buy-big-data-integration-platforms) - [How to Buy Big Data Integration Platforms?](#how-to-buy-big-data-integration-platforms) - [What Do Big Data Integration Platforms Cost?](#what-do-big-data-integration-platforms-cost) - [Implementation of Big Data Integration Platforms](#implementation-of-big-data-integration-platforms) - [Big Data Integration Platforms Trends](#big-data-integration-platforms-trends) - [Big Data Integration Platforms FAQs](#big-data-integration-platforms-faqs) - [Most Popular FAQs](#most-popular-faqs) - [Small Business FAQs](#small-business-faqs) - [Enterprise FAQs](#enterprise-faqs) [ ### Big Data Integration Platforms Topics Expand/Collapse ](#) - [What are Big Data Integration Platforms?](#what-are-big-data-integration-platforms) - [What are the Common Features of Big Data Integration Platforms?](#what-are-the-common-features-of-big-data-integration-platforms) - [What are the Benefits of Big Data Integration Platforms?](#what-are-the-benefits-of-big-data-integration-platforms) - [Who Uses Big Data Integration Platforms?](#who-uses-big-data-integration-platforms) - [Challenges with Big Data Integration Platforms](#challenges-with-big-data-integration-platforms) - [Which Companies Should Buy Big Data Integration Platforms?](#which-companies-should-buy-big-data-integration-platforms) - [How to Buy Big Data Integration Platforms?](#how-to-buy-big-data-integration-platforms) - [What Do Big Data Integration Platforms Cost?](#what-do-big-data-integration-platforms-cost) - [Implementation of Big Data Integration Platforms](#implementation-of-big-data-integration-platforms) - [Big Data Integration Platforms Trends](#big-data-integration-platforms-trends) - [Big Data Integration Platforms FAQs](#big-data-integration-platforms-faqs) - [Most Popular FAQs](#most-popular-faqs) - [Small Business FAQs](#small-business-faqs) - [Enterprise FAQs](#enterprise-faqs) ## Learn More About Big Data Integration Platforms ### What are Big Data Integration Platforms? Big data integration is defined as a process within the data lifecycle that involves extracting data from heterogeneous sources and combining it to obtain insightful unified information which can aid in better decision making.  Big data integration platforms are the tools that allow data to be extracted from various data sources and then sort and process it. There is a huge volume of data generated from various sources daily. Organizations are trying to capture value out of this data, and fully managed big data integration platforms with no indexing or tuning required have made that easier for teams without a large data engineering staff. Most of the data comes in an unstructured format. Required data is often distributed across various sources like IoT endpoints, applications, communications, or provided by third parties. #### What Types of Big Data Integration Platforms Exist? The end goal of a big data integration platform is to transfer and unify data from disparate sources. Data managers can get a better understanding of various methods of achieving this goal by understanding the different types of data integration software. They can decide which type of platform suits them the most:  **Middleware data integration** Middleware is a software that acts as a binding material for two different systems. It connects various applications and transfers data from application to database. Middleware is widely in use for application integration and data management. When an organization is integrating legacy systems with modern ones, middleware is used.  **Data consolidation** This term is interchangeably used with data integration. Data consolidation means combining data from all disparate sources. It also removes any errors before storing it in a data warehouse or data lake. Data consolidation improves data quality. **Extract, transform and load (ETL)** ETL forms the core of data integration tools even today. ETL is the process of consolidation of data in a data warehouse. It involves extracting the data from source systems, transforming it into the required format, and loading it to the target system. **Enterprise data integration** While big data integration is a broader term, enterprise data integration refers to the centralization of data across multiple organizations. This is usually done when the organizations go through mergers and acquisitions.  ### What are the Common Features of Big Data Integration Platforms? Based on G2 reviews, data analysts and data engineers evaluate big data integration platforms by comparing connector breadth, data transformation capabilities, and governance controls. Big data integration software is one way for any organization to make informed decisions. Below are key features of big data integration platforms: **Big data connectors:** Many applications use more than one database nowadays. Data connectors make it possible to move data from one database to another. Organizations use big data connectors to filter and transform data in a proper structure for querying and analyzing purposes. Organizations can benefit from the scalability and real-time data transmissions unlike that of traditional batches. With cloud-based and data-driven businesses gaining popularity, advanced data integration in any big data integration platform helps with more agile integrations, without constant schema changes. IPaaS provides pre-built big data connectors, business rules, and maps, which help organize integration flows.  **Data transformation:** Data transformation is the process of changing data from one format structure into another. Organizations use this tool to organize the data better by making it compatible with other data, joining data, and so on. The processes such as data integration, data migration, data warehousing/data storage, and data wrangling all may involve data transformation. **Leverage data from unconventional sources of big data:** This is one of the key features of any efficient big data integration platform. Common file formats like PDFs are usually supported by data integration tools. The advanced feature of leveraging data from unconventional sources supports file formats like COBOL, email sources, and XML/JSON files. Organizations use this feature to obtain streamlined data analysis. **Data virtualization:** Organizations benefit from this feature by getting access to a unified view of various disparate systems. There is no physical movement of data to and from databases. The feature gives organizations real-time access to their data without exposing the technical details of the source systems. **Data quality:** This feature is central to all the big data integration platforms. When data is of excellent quality, it is easier to process and analyze, ultimately helping organizations to make better decisions. **Database integration:** Database technology aids in data storage and has evolved over the years. Relational, NoSQL, hierarchical, and many more are types of databases. NoSQL database is also known as a non-relational database. Database integration is usually done in cases of mergers and acquisitions. Two individual databases are integrated for a better understanding of new business. **Big data management:** It is the organization, administration, and governance of large volumes of structured and unstructured data. Data governance is a major part of data management. A big data governance strategy plays a key role in determining how the business will benefit from available resources. Organizations leverage this feature to ensure a high level of data quality.  **Data processing:** The feature manipulates data by collecting and combining it to obtain usable information. With big data migrating to the cloud, the benefits of cloud data processing can be reaped by small and large organizations alike. **Application programming interface (API):** This feature connects one system to another via APIs, allowing the data exchange between those two systems. It facilitates seamless connectivity between devices and programs. **Data warehouse:** This is a part of the data integration process which deals with cleansing, formatting, and data storage. One of the important implementations of big data integration is building a data warehouse. It is done by merging systems to unify the data from disparate sources. Technically data warehouses perform queries and analysis. ### What are the Benefits of Big Data Integration Platforms? Businesses today are data-driven. Hence, it is important to clean, process, and organize this data for better decision-making. Following are the benefits of implementing big data integration platforms at organizations:  **Reducing the complexity of big data:** In any organization, the more the number of applications, the more are the number of interfaces. Big data can be difficult to manage at times. However, big data integration software helps in managing complexity, making easier delivery of data to any system, and streamlining the connections. It begins with defining business-critical data; data related to customers, products, sites, and suppliers. The overall process might involve updating, collating, and refining data to form a uniform understanding of the same.  **Scalability:** Big data is primarily unstructured and requires real-time analysis. Advanced big data tools in association with cloud computing aid in connecting the data with real-time events and automate resource allocation based on integration activities. When organizations have scalable data platforms, they are also prepared for potential growth in their data needs. **Better decision making:** Organizations often deal with a variety of data from disparate sources. Data integration helps managers understand the dynamics of their business and anticipate shifts in the market. Data entered manually can often have flaws and thus poor insights going further. Integration platforms help in obtaining up-to-date data, thus facilitating faster and higher quality decision making. When data is unified, it is available for everyone in the organization to access. This boosts transparency, collaboration, and ultimately maximizes data value.  **Cost optimization:** Integration platforms create a centralized software architecture that connects to system and software and allows transporting data seamlessly. This focuses on eliminating inefficiencies caused due to using multiple software within an organization. This brings down the cost required for storing, processing, and analyzing large amounts of data. **Data governance:** This system helps in understanding the executives in charge of data assets in an organization.  ### Who Uses Big Data Integration Platforms? **Data analysts and data scientists:** These employees are generally the main users of big data integration tools. They use the software to gather a deeper understanding of business-critical data. These teams may be tasked with data preparation, cleansing, and data processing for further analysis. **Marketing teams:** Marketing teams often run different types of campaigns, including email marketing, digital advertising, or even traditional advertising campaigns. The data that is error free and insightful helps the marketing team to execute successful campaigns and strategies. Big data integration helps the marketing teams promote the company or its product to the target audience. **Finance teams:** Finance teams leverage data integration platforms to gain insight and understanding into the factors that impact an organization's business. Finance teams require real-time data for obtaining actionable insights which is possible using advanced data integration software. By integrating financial data with other operations data, accounting and finance teams pull actionable insights that might not have been uncovered through the use of traditional tools. #### Software Related to Big Data Integration Platforms Related solutions that can be used together with data integration include: **Metadata-driven data integration software:** Big data integration software can handle a variety of data. However, when used with powerful metadata, it can streamline the creation and management of BI reporting. Metadata repository provides a view and analyses the movement of data around the organization. [Data management platforms](https://www.g2.com/categories/data-management-platforms) **:** This category of software is used to gather, analyze, and store big data. Data management platforms help organizations leverage big data from various sources in real time leading to effective customer engagement. [Data replication software](https://www.g2.com/categories/data-replication) **:** Data replication can be one-time or an ongoing process. This software aims at keeping all the members of the organization on the same page. Data replication involves copying data from one server to a database on another server. [Big data analytics software](https://www.g2.com/categories/big-data-analytics) **:** Data Analytics platforms are a great aid to any organization with the need for timely data visualization of high-level analytics. Many industries target their customers using data analytics which helps the companies provide a customized experience and meet customer expectations. **Application integration software:** Application integration, like data integration, works in batches; this leaves gaps in taking quick actions. Organizations can benefit from moving data in real time with application integration to easy access and quicker actions. ### Challenges with Big Data Integration Platforms **Managing large data volume:** The exponential growth of data from various sources is one of the biggest challenges of big data integration. This further creates issues with the retention of this data. Sometimes data runs on multiple platforms—a combination of on-premises and cloud hosting. This gives rise to complexity and managing can become difficult. **Manual data integration tasks:** In many organizations, data scientists are the employees finding and preparing the data, which leaves an equivalent to only a week’s time for actual data science tasks and analytical work. This has made enterprises look for tools to automate ingestion and integration. **Growth of heterogeneous data:** Heterogeneous data is a group of data with non-similar data types. Data is collected in different formats—structured, unstructured, and semi-structured. Integrating all these disparate data types is a tedious process and would need a proper ETL tool. Data is mostly handled by various data handling systems and it may not be in the same format. **Issues with data quality:** Incompatible or invalid data may be present in the data obtained from disparate sources. Businesses might not be aware of this, and the analytics might show insights with this incompatible data which could have severe repercussions. The insights provided by data analytics could potentially be misleading. The quality of gathered data is kept in check by appointing an executive for data management. This manual job can be time consuming for huge volumes of data. ### Which Companies Should Buy Big Data Integration Platforms? **Retail:** This industry is the most common one to use big data software. They want to attract more customers to their business. For that, they need to correctly anticipate what the customers want. Accurate insights can help companies to identify their target customers as well as build on their competitive advantage. **Logistics:** Data Integration brings different systems together by combining data and functions. Data in the transportation and logistics industry is stored in on-premises ERP and cloud-based CRM systems. Big data integration solutions help organizations overcome challenges like traffic congestion and mismanagement of capacity using automated fleet management and cloud-based analytics. Business processes are optimized and transcription errors are also reduced. **Education:** Data privacy and security are of utmost importance in the education industry. Big data tools are changing the educational scenario altogether. Cutting-edge technology can help make better educational assessments.  **Banking and finance:** Data integration helps banks in providing better customer experience, cross-selling, customer retention, and overall profitability. Big data integration helps in fraud detection and compliance. **Construction:** Large infrastructure projects are huge in volume. While construction is one of the least digitized industries, organizations are now realizing the importance of the data that is generated and that it should be leveraged for obtaining better results. Using big data integration platforms, companies can combine design and construction data so that every department remains on the same page. This leads to better tracking of project design data being used at the construction site. **Healthcare:** Big data platforms are critical to the healthcare industry. The data in healthcare is unstructured and data integration can prove useful in obtaining valuable insights. The ultimate goal of data integration solutions in this industry is to improve the quality and cost of healthcare for patients and researchers. ### How to Buy Big Data Integration Platforms? #### Requirements Gathering (RFI/RFP) for Big Data Integration Platforms If a company is just starting out and looking to purchase the first big data integration platform, or maybe an organization needs to update a legacy system--wherever a business is in its buying process, g2.com can help select the best big data integration software for the business. The particular business pain points might be related to all of the manual work that must be completed. If the company has amassed a lot of data, the need is to look for a solution that can grow with the organization. Users should think about the pain points and jot them down; these should be used to help create a checklist of criteria. Additionally, the buyer must determine the number of employees who will need to use the big data integration tool, as this drives the number of licenses they are likely to buy. Taking a holistic overview of the business and identifying pain points can help the team springboard into creating a checklist of criteria. The checklist serves as a detailed guide that includes both necessary and nice-to-have features including budget features, number of users, integrations, security requirements, cloud or on-premises solutions, and more. Depending on the scope of the deployment, it might be helpful to produce an RFI, a one-page list with a few bullet points describing what is needed from a big data integration platform. #### Compare Big Data Integration Platforms Products **Create a long list** From meeting the business functionality needs to implementation, vendor evaluations are an essential part of the software buying process. For ease of comparison after all demos are complete, it helps to prepare a consistent list of questions regarding specific needs and concerns to ask each vendor. **Create a short list** From the long list of vendors, it is helpful to narrow down the list of vendors and come up with a shorter list of contenders, preferably no more than three to five. With this list in hand, businesses can produce a matrix to compare the features and pricing of the various big data integration solutions. **Conduct demos** To ensure the comparison is thorough, the user should demo each solution on the shortlist with the same use case and datasets. This will allow the business to evaluate like for like and see how each vendor stacks up against the competition. #### Selection of Big Data Integration Platforms **Choose a selection team** Before getting started, it's crucial to create a team that will work together throughout the entire process, from identifying pain points to implementation. The software selection team should consist of members of the organization who have the right interest, skills, and time to participate in this process. A team of three to five people with roles such as the main decision maker, project manager, process owner, system owner, or staffing subject matter expert, as well as a technical lead, IT administrator would suffice. In smaller companies, the vendor selection team may be smaller, with fewer participants multitasking and taking on more responsibilities. **Negotiation** As data integration platforms are all about the data, the user must make sure that the selection process is data driven as well. The selection team should compare important data like pricing metrics of a particular vendor, the stage that buyer organization is in, and also terms and conditions of the organization. **Final decision** It is imperative to open up a conversation regarding pricing and licensing. For example, the vendor may be willing to give a discount for multi-year contracts or for recommending the product to others. ### What Do Big Data Integration Platforms Cost? Data Integration software is available both on-premises and on cloud. The cost per type changes given there are certain factors for each type to consider. The organizations that consider deploying on-premises software are liable for costs associated with server hardware, power consumption, and space. Whereas software using the cloud can be charged for the resources it uses and prices go up or down depending on how much of the software is consumed.  #### Return on Investment (ROI) Organizations buy big data integration platforms with an expectation of a certain ROI. Although there are ways to directly calculate ROIs, it could be a little daunting to use those here. It entirely depends on the intricacy of the project and ultimately the software itself. ROI can be further looked at from an IT perspective and a business perspective. The ROI on IT infrastructure, staffing, expertise-building, and services cost is calculated. Whereas, for business, time investments, outside investments (the cost related to external partners involved in the project), and opportunity costs are treated as important. ### Implementation of Big Data Integration Platforms **How are Big Data Integration Platforms Implemented?** It is necessary to define the goals to be achieved using a big data integration platform. This will help measure the success of target projects for which big data integration software will be used. Large organizations have data in large volumes from heterogeneous data sources, hence it is better to hire an external party for implementing the software. Connectivity between systems is ensured during the process. With a rich experience throughout the years, the specialists from these consultancy firms can guide the businesses in connecting and consolidating their data effectively by helping the company to identify the best vendors in the space that would suit their business needs and goals. **Who is Responsible for Big Data Integration Platforms Implementation?** Data integration implementation can be a tedious process. In such times, it is advisable to have vendor support throughout the implementation. The team size could range from moderate to large depending on the complexity of the software being implemented. With cross-functional teams, it is possible to streamline the implementation process. Before actual use, it is always a good practice to test sample data. **What Does the Implementation Process Look Like for Big Data Integration Platforms?** The overall implementation process can be done in the following steps: - Identifying and defining the project is a step when organizations can figure out the format in which the consolidated data has to be in so that it can prove of maximum usefulness to the organization. - Reviewing the systems becomes crucial at this point. Depending on the connectivity, the consultancy specialists may advise on data connectors and/or SFTP ports to facilitate data interchange. - Defining data integration framework. - Defining how data will be processed. **When Should You Implement Big Data Integration Platforms?** Big data integration software is usually required when the organization deals with loads of data coming from disparate sources. ### Big Data Integration Platforms Trends **Hybrid integration platforms** These platforms help business users to handle highly complex data. Hybrid integration platforms integrate on-premises and cloud-based data. These platforms help in reducing costs and risks. **Integration using artificial intelligence and machine learning** The disruptive nature of today’s digital transformation has paved the way for many new developments in integration platforms. With artificial intelligence, it is possible to obtain accurate insights about customer data and thus meet up to their expectations. Machine learning helps in providing the transparency to make better decisions. **Adoption of software as a service (SaaS) and cloud** SaaS is helping traditional on-premises software to migrate to the cloud. The ease of use of cloud and SaaS enables the organizations to use data from any place, at any time, and pay for how much is used. It also eliminates the use of hardware making the infrastructure flexible.  **Blockchain for data and analytics** Blockchain technology can help in more than one way:  - Enhances security - Provides transparency - Streamlines the integration process - Simplifies communications - Eliminates the need for middlemen thus reducing the cost. ### Big Data Integration Platforms FAQs ### Most Popular FAQs #### Which big data integration software has the best reviews? Across the[](https://www.g2.com/categories/big-data-integration-platforms)[Big Data Integration Platforms](https://www.g2.com/categories/big-data-integration-platforms) category, where data engineers make up a notable share of the most trusted user reviews, the strongest ratings tend to go to platforms that turn a genuinely complex job, moving and governing data at scale, into something a team can operate without constant firefighting. - [ILUM](https://www.g2.com/products/ilum-ilum/reviews): A newer name in this data set, though it turns Spark-on-Kubernetes delivery into a repeatable practice, with CI, secrets, RBAC, cost tags, and lineage set up the same way every time. - [Orchestra](https://www.g2.com/products/orchestra-orchestra/reviews): A smaller sample so far, but its clean, modern interface and built-in agents come up repeatedly as reasons teams stick with it. - [Workato](https://www.g2.com/products/workato/reviews): Carries solid review volume at a high rating, with a clean, accessible interface even for non-technical users building a flow. #### What are the top big data processing platforms for integration? The platforms with both the largest review base and the broadest processing footprint tend to be the ones built to sit at the center of a company's entire data stack. - [Alteryx](https://www.g2.com/products/alteryx/reviews): Carries the largest review volume in this category, with a fully visual workflow that lets you watch data move through each processing step. - [Snowflake](https://www.g2.com/products/snowflake/reviews): Separates storage from compute, letting multiple teams query the same data simultaneously without one workload slowing down another. - [Google Cloud BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews): Runs entirely in the cloud with no hardware to manage, and lets teams save and share queries directly inside the platform. #### What are the top big data integration tools for hybrid environments? The strongest fits here are built specifically to bridge on-premises systems with cloud infrastructure, rather than assuming everything already lives in one place. - [Azure Data Factory](https://www.g2.com/products/azure-data-factory/reviews): Connects on-premises databases with cloud storage and analytics through built-in connectors and integration runtime options, orchestrating pipelines centrally across both environments. - [IBM StreamSets](https://www.g2.com/products/ibm-streamsets/reviews): Built for DataOps in hybrid environments specifically, with pipeline monitoring and governance for streaming workloads that need to move continuously across systems. - [AWS Glue](https://www.g2.com/products/aws-glue/reviews): Cloud-native at its core, but supports hybrid setups by connecting on-premises sources to AWS services as teams gradually shift workloads to the cloud. #### Which big data integration platform offers the fastest processing? Speed here usually comes down to architecture — whether compute and storage scale independently, or whether a pipeline gets bottlenecked waiting on infrastructure. - [Skyvia](https://www.g2.com/products/skyvia/reviews): A pipeline gets running quickly, cutting out the wait that used to come with pulling data from SaaS tools like Salesforce. - [ILUM](https://www.g2.com/products/ilum-ilum/reviews): A newer name here, but its handling of Spark workloads on Kubernetes shows up repeatedly in reviews as fast and repeatable rather than a one-off engineering project. - [Snowflake](https://www.g2.com/products/snowflake/reviews): Its separation of storage and compute is built specifically to scale workloads without one team's queries slowing down another's. #### What are the best data integration platforms? The right answer depends on the specific job, but a few platforms come up across a wide range of data integration use cases. - [Maia](https://www.g2.com/products/matillion-maia/reviews): A rich library of components and low-code pipelines make it easy to pick up even for teams new to data integration. - [SnapLogic Intelligent Integration Platform (IIP)](https://www.g2.com/products/snaplogic-intelligent-integration-platform-iip/reviews): Its library of pre-built "snaps" connects to a wide range of data sources and destinations without writing custom code for each one. - [Adverity](https://www.g2.com/products/adverity/reviews): A large number of pre-existing sources and destinations connect the same set of tools cleanly, even across different companies using it. #### Which big data integration platforms support secure data sharing without copying datasets? The distinction that matters here is physical vs. logical access: platforms built for secure sharing let another team or an outside partner query a dataset directly, rather than requiring a copy to be exported, moved, and kept in sync. - [Snowflake](https://www.g2.com/products/snowflake/reviews): Its Secure Data Sharing feature is repeatedly cited by reviewers as letting teams and external partners access datasets directly, with one reviewer specifically noting they can "share datasets across teams without copying anything." - [Denodo](https://www.g2.com/products/denodo/reviews): Its own product listing describes "unified, real-time-updated data views without expensive replication or copying of data," which is the core promise of the data virtualization approach this guide's Features section already covers. - [Cloudera](https://www.g2.com/products/cloudera/reviews): Its Unified Data Fabric is built to connect disparate data sources into one governed, secure view rather than requiring each team to maintain its own copy. #### Which big data integration platforms are most popular and most relied on for structured and unstructured data? The platforms senior data engineers reach for here aren't the ones that only handle clean, structured tables, they're the ones built to hold structured, semi-structured, and unstructured data side by side without forcing a separate system for each type. - [Snowflake](https://www.g2.com/products/snowflake/reviews): Reviewers specifically cite support for both structured and semi-structured data, including JSON and Parquet formats, within the same warehouse rather than a bolt-on for non-tabular data. - [Cloudera](https://www.g2.com/products/cloudera/reviews): Built around asserting control over data "in all forms," with an open data lakehouse designed to unify structured and unstructured sources rather than keeping them in separate silos. - [Alteryx](https://www.g2.com/products/alteryx/reviews): Reviewers describe blending genuinely different source types on a single canvas, an Excel file, a SQL database, and a cloud API, without writing custom code for each format. ### Small Business FAQs #### What is the most affordable big data integration platform for SMBs? Within the[](https://www.g2.com/categories/big-data-integration-platforms/small-business)[small business segment of Big Data Integration Platforms](https://www.g2.com/categories/big-data-integration-platforms/small-business), the platforms that come up most often are the ones built for lean teams without a large data engineering budget. - [Skyvia](https://www.g2.com/products/skyvia/reviews): A team of five running data for a 40-person SaaS company got this running quickly with a single analytics engineer, without needing a bigger budget or team. - [EazyDI](https://www.g2.com/products/eazydi/reviews): A newer name in this data set, though its low-code approach let operations and analytics teams collaborate without building custom integrations from scratch. - [5X](https://www.g2.com/products/5x/reviews): A smaller footprint so far, but its team is described as extremely supportive in transforming raw data into a structured model without a large upfront investment. #### What is the best big data integration platform for startups? Startups evaluating[](https://www.g2.com/categories/big-data-integration-platforms/small-business)[small business big data integration](https://www.g2.com/categories/big-data-integration-platforms/small-business) tools tend to prioritize a platform that a lean team can run without dedicated data engineering headcount. - [Workato](https://www.g2.com/products/workato/reviews): Builds flows that stay accessible even for non-technical people, which matters when a startup doesn't have a dedicated integration engineer yet. - [Astro by Astronomer](https://www.g2.com/products/astro-by-astronomer/reviews): Handles the infrastructure, monitoring, and upgrades behind Airflow, freeing up a small engineering team to focus on actual data work instead of managing orchestration. - [Alteryx](https://www.g2.com/products/alteryx/reviews): Its visual, no code data preparation workflow, reviewers describe it as bridging the gap between non-technical business users and data scientists, makes onboarding fast, backed by a large support community when questions come up. #### Which big data integration platform is the most user-friendly for startups? Ease of use matters most at this stage, since the person building pipelines is often the same person analyzing the results. - [Maia](https://www.g2.com/products/matillion-maia/reviews): New users pick it up quickly thanks to a simple layout and low-code pipelines that don't require deep integration experience up front. - [dbt](https://www.g2.com/products/dbt/reviews): All a team really needs is SQL, and its lineage feature makes it easy to see exactly how data flows through each transformation. - [Workato](https://www.g2.com/products/workato/reviews): Building a flow stays simple even for non-technical team members, thanks to a clean, accessible interface. #### Which big data integration tool is easiest to set up for small teams? Setup speed is one of the more differentiated ratings in this category, and small teams generally do best with a platform that skips a long implementation project. - [Peliqan](https://www.g2.com/products/peliqan/reviews): Replaced several separate tool integrations, each with its own auth and config, with one ready-to-use data foundation set up in a fraction of the time. - [Coefficient](https://www.g2.com/products/coefficient/reviews): Pulls data straight into Google Sheets and keeps it synced automatically, with no separate infrastructure for a small team to stand up. - [Skyvia](https://www.g2.com/products/skyvia/reviews): Gets a first pipeline running quickly, which matters most for a team without a dedicated engineer to spend weeks on setup. #### Which big data integration tool works best for lean teams without dedicated data engineers? Teams without a dedicated data engineering function tend to do best with platforms built around simplicity and active support rather than deep customization. - [Keboola](https://www.g2.com/products/keboola/reviews): Ease of use and simplicity stand out, with connectors that are particularly valuable for ingestion and customer support that stays genuinely active. - [Skyvia](https://www.g2.com/products/skyvia/reviews): Built for exactly this situation, a small team with one analytics engineer handling data for the whole company. - [Peliqan](https://www.g2.com/products/peliqan/reviews): Gives a lean team a ready-to-use data foundation with built-in connectors, rather than requiring separate setups for every tool. ### Enterprise FAQs #### What is best-rated big data integration software for large enterprises? Within the[](https://www.g2.com/categories/big-data-integration-platforms/enterprise)[Enterprise segment of Big Data Integration Platforms](https://www.g2.com/categories/big-data-integration-platforms/enterprise), a smaller set of platforms have the review volume from large organizations to back up a strong rating. - [Workato](https://www.g2.com/products/workato/reviews): Holds up well at the enterprise level, with the same clean, accessible interface that smaller teams rely on scaling across much larger organizations. - [Alteryx](https://www.g2.com/products/alteryx/reviews): Carries a large enterprise review base, with its visual workflow and broad integrations continuing to hold up as data volume grows. - [Snowflake](https://www.g2.com/products/snowflake/reviews): The same storage-compute separation that helps smaller teams carries over here, letting many teams query independently without stepping on each other. #### What is the most reliable big data integration tool for enterprises? Reliability at this scale tends to come down to support responsiveness and administrative control, since large organizations need both to keep pipelines running across many teams. - [Workato](https://www.g2.com/products/workato/reviews): Enterprise accounts report support and administrative scores among the strongest in the category. - [Snowflake](https://www.g2.com/products/snowflake/reviews): Its architecture keeps performance consistent even as more teams and workloads get added, which large organizations lean on for reliability. - [Astro by Astronomer](https://www.g2.com/products/astro-by-astronomer/reviews): Manages Airflow infrastructure, monitoring, and upgrades directly, cutting down on the operational surprises that hit reliability at scale. #### What is best-reviewed big data integration software for enterprise hybrid cloud environments? Enterprise hybrid rollouts depend on a platform that treats on-premises and cloud systems as one connected environment rather than two separate projects. - [Azure Data Factory](https://www.g2.com/products/azure-data-factory/reviews): Purpose-built to orchestrate pipelines centrally across on-premises databases and cloud storage, which is exactly the coordination large hybrid rollouts need. - [IBM StreamSets](https://www.g2.com/products/ibm-streamsets/reviews): Its governance and pipeline monitoring are designed specifically for DataOps in hybrid environments at enterprise scale. - [AWS Glue](https://www.g2.com/products/aws-glue/reviews): Supports hybrid setups directly, letting large organizations connect on-premises sources into AWS as they migrate workloads gradually rather than all at once. #### Which big data integration platform offers the strongest data lineage and governance for enterprise teams? Governance needs at this scale go beyond basic access control — enterprise teams need to trace exactly where data came from and how it changed along the way. - [dbt](https://www.g2.com/products/dbt/reviews): Its lineage feature makes it possible to trace exactly how data flows through every transformation, which large teams rely on for audit and troubleshooting. - [ILUM](https://www.g2.com/products/ilum-ilum/reviews): A smaller footprint at enterprise scale so far, but it bakes RBAC, secrets, cost tags, and lineage into every workspace the same way, rather than leaving governance as an afterthought. - [EazyDI](https://www.g2.com/products/eazydi/reviews): Balances automation with governance and analytics readiness, with data profiling that helps large teams catch issues before they spread downstream. #### Which big data integration platform is best for orchestrating large-scale enterprise workflows? At enterprise scale, orchestration means coordinating many interdependent pipelines across teams rather than scheduling a handful of standalone jobs. - [Control-M](https://www.g2.com/products/control-m/reviews): A single, unified view lets teams track workflows across multiple platforms at once, cutting down manual monitoring and catching operational bottlenecks early. - [Astro by Astronomer](https://www.g2.com/products/astro-by-astronomer/reviews): Makes managing Airflow at scale effortless by handling infrastructure, monitoring, and upgrades that would otherwise fall on an internal platform team. - [Azure Data Factory](https://www.g2.com/products/azure-data-factory/reviews): Centralizes orchestration across data-driven workflows, giving large organizations one place to schedule and monitor pipelines spanning multiple systems.