# Best Big Data Integration Platforms - Page 4 *By [Shalaka Joshi](https://research.g2.com/insights/author/shalaka-joshi)* 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 Big Data Integration Platforms at a Glance | # | Product | Rating | Best For | What Users Say | |---|---------|--------|----------|----------------| | 1 | [Google Cloud BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews) | 4.5/5.0 (1,144 reviews) | Serverless SQL analytics across Google-native data pipelines | "[Easy-to-Use Cloud Tool with Shareable, Saved Queries](https://www.g2.com/survey_responses/google-cloud-bigquery-review-12958418)" | | 2 | [Alteryx](https://www.g2.com/products/alteryx/reviews) | 4.6/5.0 (849 reviews) | No-code ETL and multi-source data blending | "[Alteryx Streamlines Data Prep with an Intuitive Drag-and-Drop Workflow Builder](https://www.g2.com/survey_responses/alteryx-review-13000974)" | | 3 | [Snowflake](https://www.g2.com/products/snowflake/reviews) | 4.5/5.0 (708 reviews) | Multi-workload analytics with compute-storage separation | "[Snowflake Simplifies Data Management at Scale](https://www.g2.com/survey_responses/snowflake-review-12898129)" | | 4 | [Workato](https://www.g2.com/products/workato/reviews) | 4.7/5.0 (749 reviews) | Cross-application data orchestration with low-code recipes | "[The Platform That Grew With Us](https://www.g2.com/survey_responses/workato-review-12941177)" | | 5 | [Azure Data Factory](https://www.g2.com/products/azure-data-factory/reviews) | 4.6/5.0 (95 reviews) | Azure-native ETL orchestration across hybrid data sources | "[Low-Code Drag-and-Drop That Makes Development Easy for Developers and Business Users](https://www.g2.com/survey_responses/azure-data-factory-review-12746463)" | | 6 | [SnapLogic Intelligent Integration Platform (IIP)](https://www.g2.com/products/snaplogic-intelligent-integration-platform-iip/reviews) | 4.4/5.0 (373 reviews) | Low-code ETL pipeline building across hybrid environments | "[Effortless Integration, Minor Long-Run Hiccups](https://www.g2.com/survey_responses/snaplogic-intelligent-integration-platform-iip-review-10786237)" | | 7 | [Maia](https://www.g2.com/products/matillion-maia/reviews) | 4.5/5.0 (120 reviews) | — | "[Maia Makes Onboarding Fast with an Intuitive UI and Low-Code Pipelines](https://www.g2.com/survey_responses/maia-review-12942268)" | | 8 | [Amazon Redshift](https://www.g2.com/products/amazon-redshift/reviews) | 4.3/5.0 (371 reviews) | AWS-native analytical data warehousing at petabyte scale | "[Powerful Analytics Tool with Some Flexibility Limitations](https://www.g2.com/survey_responses/amazon-redshift-review-12781722)" | | 9 | [5X](https://www.g2.com/products/5x/reviews) | 4.9/5.0 (81 reviews) | End-to-end data stack consolidation with managed dbt orchestration | "[A reliable and scalable data partner](https://www.g2.com/survey_responses/5x-review-11889175)" | | 10 | [Astro by Astronomer](https://www.g2.com/products/astro-by-astronomer/reviews) | 4.5/5.0 (135 reviews) | Managed Airflow orchestration with infrastructure-free pipeline delivery | "[Asro literally assists in data engineering work, making it easier and more productive.](https://www.g2.com/survey_responses/astro-by-astronomer-review-8519803)" | ## 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=15884&focus%5B%5D=52204&focus%5B%5D=2975&focus%5B%5D=41374&focus%5B%5D=1243833) Highlighted products: Google Cloud BigQuery, Alteryx, Snowflake, Workato, Azure Data Factory, SnapLogic Intelligent Integration Platform (IIP), Maia, and 5X. 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=workato&focus%5B%5D=azure-data-factory&focus%5B%5D=snaplogic-intelligent-integration-platform-iip&focus%5B%5D=matillion-maia&focus%5B%5D=5x) ## How Many Big Data Integration Platforms Products Does G2 Track? **Total Products under this Category:** 129 ### Category Stats (Jul 2026) - **Average Rating**: 4.52/5 The average rating of products in this category, based on all submitted ratings - **Top Trending Product**: Control-M (+0.39%) - Among all products in this category, Control-M recorded the largest rating increase compared to last month *Last updated: July 23, 2026* ## How Does G2 Rank Big Data Integration Platforms Products? **Why You Can Trust G2's Software Rankings:** - 30 Analysts and Data Experts - 9,500+ Authentic Reviews - 129+ 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. --- **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&secure%5Bcategory_id%5D=1186&secure%5Bchosen_at%5D=2026-07-23T15%3A54%3A10Z&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=llm_category_page&secure%5Bsource_url%5D=https%3A%2F%2Fwww.g2.com%2Fcategories%2Fbig-data-integration-platforms&secure%5Btoken%5D=d80d8dbc9fe2bbe81b6fa51bc624d4d4e42451860149d75951b864f0572d4af7&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) --- ## What Are the Top-Rated Big Data Integration Platforms Products in 2026? ### 1. [Megaladata](https://www.g2.com/products/megaladata/reviews) The low code Megaladata platform empowers business users by making advanced analytics accessible. - Visual design of complex data analysis models with no involvement of the IT department and no need for programming. - Over 60 ready-to-use processing components. - Easy integration with various sources. - Fast processing of large datasets achieved through in-memory computing and parallelism. - Reusable components that facilitate accumulation of business expertise. - Advanced visualization — OLAP cubes, tables, charts, and other specialized tools. Megaladata minimizes the time between hypothesis testing and a fully functional business process. **Average Rating:** 4.9/5.0 **Total Reviews:** 8 **How Do G2 Users Rate Megaladata?** - **Quality of Support:** 9.5/10 (Category avg: 8.9/10) - **Ease of Use:** 9.0/10 (Category avg: 8.8/10) **Who Is the Company Behind Megaladata?** - **Seller:** [Megaladata](https://www.g2.com/sellers/megaladata) - **HQ Location:** Neu-Isenburg, DE - **Twitter:** @megaladata_com (5 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/megaladata (5 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 88% Small-Business, 13% Mid-Market #### What Are Recent G2 Reviews of Megaladata? **"[Reusable Components and Nice Performance](https://www.g2.com/survey_responses/megaladata-review-12780960)"** **Rating:** 5.0/5.0 stars *— Vitali M.* [Read full review](https://www.g2.com/survey_responses/megaladata-review-12780960) --- **"[Megaladata is a platform for any time of on-time analytics](https://www.g2.com/survey_responses/megaladata-review-12752778)"** **Rating:** 5.0/5.0 stars *— Vartan G.* [Read full review](https://www.g2.com/survey_responses/megaladata-review-12752778) --- ### 2. [Qlik Compose](https://www.g2.com/products/qlik-compose/reviews) Qlik Compose comes in two offerings: Qlik Compose for Data Warehouses and Qlik Compose for Data Lakes. Qlik Compose for Data Warehouse automates and streamlines the design, creation, loading, management, and update of data warehouses including Amazon Redshift, Azure Synapse, Google BigQuery, Snowflake and Oracle. Qlik Compose for Data Lakes automates the process of providing continuously updated, accurate, and trusted data to big data platforms like Apache Hadoop, Cloudera Customer Data Platform and Databricks Unified Data Analytics Platform. **Average Rating:** 4.5/5.0 **Total Reviews:** 3 **How Do G2 Users Rate Qlik Compose?** - **Quality of Support:** 8.3/10 (Category avg: 8.9/10) - **Ease of Use:** 8.3/10 (Category avg: 8.8/10) **Who Is the Company Behind Qlik Compose?** - **Seller:** [Qlik](https://www.g2.com/sellers/qlik) - **Year Founded:** 1993 - **HQ Location:** Radnor, PA - **Twitter:** @qlik (64,130 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/10162/ (4,551 employees on LinkedIn®) - **Phone:** 1 (888) 994-9854 **Who Uses This Product?** - **Company Size:** 50% Enterprise, 50% Mid-Market #### What Are Qlik Compose's Pros and Cons? **Pros:** - Automation (2 reviews) - Ease of Use (2 reviews) - ETL Efficiency (2 reviews) - Solution Efficiency (1 reviews) - Time-saving (1 reviews) **Cons:** - Data Management (1 reviews) - Error Reporting (1 reviews) - Learning Curve (1 reviews) - Not User-Friendly (1 reviews) - Poor Documentation (1 reviews) ### What Do G2 Reviewers Say About Qlik Compose? *AI-generated summary from verified user reviews* **Pros:** - Users highlight the **automation capabilities** of Qlik Compose, significantly reducing manual efforts in data management processes. - Users find Qlik Compose's **ease of use** beneficial for automating data processes, significantly reducing manual effort and time. - Users praise Qlik Compose for its **efficient ETL automation** , significantly reducing manual effort in data warehousing. - Users value the **solution efficiency** of Qlik Compose, significantly decreasing efforts and accelerating dataset creation for analytics. - Users value the **time-saving automation** of Qlik Compose, streamlining dataset creation for quicker analytics. **Cons:** - Users note the lack of **support for aggregated fact and state-oriented data marts** , which limits flexibility in data management. - Users encounter **limitations in error reporting** , particularly with unsupported features like custom ETLs and clustering keys. - Users find the **learning curve challenging** , needing documentation and hands-on experience for effective onboarding with Qlik Compose. - Users find Qlik Compose **not user-friendly** due to lack of support for key data management features. - Users find the **poor documentation** of Qlik Compose challenging for onboarding new users effectively. #### What Are Recent G2 Reviews of Qlik Compose? **"[Simplify Complex Data Workflows](https://www.g2.com/survey_responses/qlik-compose-review-11057656)"** **Rating:** 4.5/5.0 stars *— Soumava S.* [Read full review](https://www.g2.com/survey_responses/qlik-compose-review-11057656) --- **"[Qlik Compose Review](https://www.g2.com/survey_responses/qlik-compose-review-8464492)"** **Rating:** 4.0/5.0 stars *— Verified User in Pharmaceuticals* [Read full review](https://www.g2.com/survey_responses/qlik-compose-review-8464492) --- #### What Are G2 Users Discussing About Qlik Compose? - [What is Qlik Compose used for?](https://www.g2.com/discussions/what-is-qlik-compose-used-for) ### 3. [Rayven](https://www.g2.com/products/rayven/reviews) What is Rayven? Rayven is an operational software platform that delivers an AI data fabric - connecting every system, data source, and data stream across a business into a single managed environment, then letting teams build custom apps, AI agents, workflow automations, dashboards, and MCP servers for direct AI model connectivity on top. It is the platform for organisations that need to act on operational data in real-time, deploy AI that actually works in production + build software that fits the way their business operates - without replacing existing systems or waiting 18 months for results. The Problem Rayven Solves Most organisations already have the systems and data they need. The challenge is fragmentation. ERP systems, SCADA platforms, IoT devices, databases, cloud tools, and files all generate valuable data - but it sits in silos, impossible to act on in real-time. The result: manual reporting, disconnected workflows, and AI projects that fail before reaching production. Industry research shows 95% of AI projects never ship - most because the underlying data layer is not clean, connected, or ready. Rayven builds that foundation first, then activates it. The Rayven Platform Rayven operates across five unified layers, delivered as a single managed environment: - Integration: More than 600 pre-built connectors pull data from IT, OT, IoT, files, APIs, databases, and data streams - bidirectionally, in real-time. Connects industrial protocols (OPC UA, Modbus, MQTT, BACnet) alongside cloud platforms, business systems, and proprietary tools. - Data: All connected data lands in a single managed platform - structured, governed + AI-ready. Real-time processing, ETL pipelines, data lakes, and AI model training handled in one place. - Execution: Automation rules, predictive models + agentic AI run directly on live operational data. Rules-based logic, machine learning, and goal-seeking autonomous agents all operate in one execution environment. - Presentation: Custom apps, dashboards, portals, conversational interfaces, and mobile applications deployed from the same platform - built for specific workflows, not generic reporting. - Security, Governance + Hosting: Role-based access control, data lineage, audit trails, AES-256 encryption, data residency controls, and enterprise-grade infrastructure - included as standard. AI Capabilities Rayven includes ten native AI capabilities built directly into the platform: 1. Custom AI agents (goal-seeking, action-taking) 2. Predictive analytics and machine learning 3. Conversational analytics 4. Real-time and continuous model training 5. AI-led workflow automation 6. Multimodal processing (documents, video, images, audio) 7. Anomaly and risk detection 8. Forecasting and optimisation 9. Vision and edge AI inference 10. Generative operational summaries MCP server support enables direct connectivity for AI models including Claude, GPT, and others. What Gets Built Rayven customers build and deploy: - Custom operational apps and field applications. - AI agents that monitor conditions, detect anomalies + take corrective action autonomously. - Predictive maintenance and performance models running on live plant data. - Real-time dashboards and executive reporting tools. - Workflow automations spanning IT and OT systems. - Customer and partner portals. - Data pipelines and integration layers. - White-label software products delivered under partner brands. Key Differentiators vs. Point solutions (Zapier, MuleSoft, Power BI, DataRobot): point solutions do one thing well but force teams to stitch together five separate tools to cover integration, data, AI, presentation, and governance. Rayven replaces the stack. vs. Traditional enterprise platforms (SAP, Oracle, Palantir): enterprise platforms take 12-18 months and seven figures to implement. Rayven deploys in two to 12 weeks at fixed scope and fixed price. vs. Low-code app builders (Mendix, OutSystems): app builders handle the presentation layer but do not solve the underlying data and integration problem. Rayven covers the full stack. Technology Compatibility Rayven is fully technology-agnostic and works alongside existing systems: - Cloud platforms: Microsoft Azure, Google Cloud + AWS - Business systems: SAP, Salesforce, Oracle, and Microsoft 365 - OT platforms: Siemens, Rockwell, Schneider Electric, and Ignition - Industrial protocols: OPC UA, Modbus, MQTT, BACnet, and EtherNet/IP - IoT devices: any device with a data output - Custom and proprietary systems via API, webhook, or direct connector Nothing needs to be replaced. Every existing investment is preserved. Who Uses Rayven Rayven serves businesses from growth-stage to large enterprise across 24+ industries globally - manufacturing, mining, construction, infrastructure, logistics, utilities, financial services, healthcare, agriculture, government, and more. Customers across Australia, Europe, North America, South America, and Africa. Named customers include Anglo American, Fulton Hogan, Glencore, Vodafone, NSW Ports, CSIRO, Collective Intelligence, Ramjack, and AngloGold Ashanti. Delivery Options - DIY: Full platform access. Internal teams build and deploy independently. - Done-For-You: Australia-based delivery team. Fixed scope, fixed price, two to 12 weeks from brief to go-live. - Hybrid: Guided delivery first, with the customer's team taking increasing ownership over time. By the Numbers - More than 600 pre-built connectors. - Ten native AI capabilities. - More than 240 deployments live globally. - Rated 5/5 across more than 140 independent reviews. - Deploys 66% faster than traditional development. - Two to 12 weeks to first working solution. - Rayven exists to close the gap: 95% of AI projects never reach production (industry average). **Average Rating:** 4.9/5.0 **Total Reviews:** 29 **How Do G2 Users Rate Rayven?** - **Quality of Support:** 9.9/10 (Category avg: 8.9/10) - **Ease of Use:** 9.9/10 (Category avg: 8.8/10) **Who Is the Company Behind Rayven?** - **Seller:** [Rayven](https://www.g2.com/sellers/rayven) - **Year Founded:** 2016 - **HQ Location:** Sydney, AU - **Twitter:** @RayvenIOT (56 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/rayveniot/ (33 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Retail - **Company Size:** 69% Mid-Market, 52% Small-Business #### What Are Rayven's Pros and Cons? **Pros:** - Ease of Use (61 reviews) - Features (49 reviews) - Automation (44 reviews) - Customization (42 reviews) - Data Management (36 reviews) **Cons:** - Learning Curve (32 reviews) - Difficult Learning (30 reviews) - Learning Difficulty (25 reviews) - Complex Setup (21 reviews) - Setup Complexity (19 reviews) ### What Do G2 Reviewers Say About Rayven? *AI-generated summary from verified user reviews* **Pros:** - Users commend Rayven's **ease of use** , highlighting effortless automation and streamlined integration through intuitive drag-and-drop features. - Users appreciate Rayven's **robust handling of large-scale data** and advanced AI capabilities, enhancing operational efficiency and flexibility. - Users praise Rayven for its **exceptional automation** capabilities, significantly streamlining data workflows and enhancing operational efficiency. - Users appreciate Rayven's **customization capabilities** , allowing tailored solutions that enhance integration and streamline operations efficiently. - Users appreciate Rayven's **robust data management** , enabling real-time processing and integration across complex systems with ease. **Cons:** - Users find the **learning curve steep** initially, requiring time and guidance to fully grasp all features. - Users find **difficult learning** curves with Rayven's features, requiring time and guidance for smoother onboarding experiences. - Users experience a **steep learning curve** initially, requiring time and additional resources to fully understand the platform. - Users find the **complex setup** challenging, especially with advanced features and multi-site deployments requiring careful planning. - Users note the **setup complexity** of Rayven, requiring assistance for advanced integrations and lengthy initial configurations. #### What Are Recent G2 Reviews of Rayven? **"[Seamless Automation and Predictive Maintenance with Rayven](https://www.g2.com/survey_responses/rayven-review-12211094)"** **Rating:** 5.0/5.0 stars *— Keith N.* [Read full review](https://www.g2.com/survey_responses/rayven-review-12211094) --- **"[Rayven's Low-Code Platform is the Fastest Way to Build and Scale Intelligent Apps](https://www.g2.com/survey_responses/rayven-review-11780301)"** **Rating:** 5.0/5.0 stars *— John M.* [Read full review](https://www.g2.com/survey_responses/rayven-review-11780301) --- ### 4. [Sesame Software](https://www.g2.com/products/sesame-software-sesame-software/reviews) Sesame Software is a comprehensive data management solution designed to assist organizations in backing up, exporting, replicating, and transferring data from various systems, including Salesforce and NetSuite, into databases, cloud storage, and other downstream systems. This suite of tools is tailored to support critical functions such as data protection, reporting, analytics, compliance, migration, and long-term data access, ensuring that businesses can effectively manage their data assets. The target audience for Sesame Software includes businesses of all sizes that rely on cloud applications and databases for their operations. Organizations seeking to safeguard their data from accidental loss or corruption, maintain compliance with regulatory standards, or streamline their data workflows will find significant value in these solutions. Specific use cases range from protecting Salesforce data against unintended deletions to exporting NetSuite data for compliance and reporting purposes. The versatility of Sesame Software makes it an essential resource for IT departments, data analysts, and compliance officers alike. One of the standout features of Sesame Software is its Salesforce Backup & Recovery solution, which is designed to protect Salesforce data from various risks, including accidental deletions and system errors. This solution offers automated full and incremental backups with flexible scheduling options, allowing users to monitor backup health and job activity through a centralized dashboard. The ability to restore data from specific backup snapshots, whether through full restores or selective record-level recovery, adds an additional layer of security and control for users. Backup history and logs further support auditing and troubleshooting, ensuring that organizations can maintain oversight of their data management processes. In addition to backup capabilities, Sesame Software provides robust data replication features that enable organizations to keep systems synchronized and support analytics and reporting. The automated replication jobs can be monitored, with logs available for tracking job status and errors, facilitating seamless data movement between systems. Furthermore, the platform includes tools for building data pipelines and ETL (extract, transform, load) workflows without the need for coding, allowing users to prepare data for reporting and analytics efficiently. Data migration is another critical aspect of Sesame Software, with automated processes that facilitate the transfer of data from source systems to target platforms while maintaining data integrity. The NetSuite Data Export feature allows organizations to export data into external databases or cloud storage, capturing both standard and custom objects while preserving schema and historical integrity. Supported destinations include a variety of relational databases and cloud storage platforms, making it easier for organizations to manage their data across different environments. Overall, Sesame Software stands out for its wide range of connectors and its ability to simplify complex data management tasks without the need for custom coding. **Average Rating:** 4.3/5.0 **Total Reviews:** 45 **How Do G2 Users Rate Sesame Software?** - **Has the product been a good partner in doing business?:** 8.7/10 (Category avg: 8.9/10) - **Quality of Support:** 8.8/10 (Category avg: 8.9/10) - **Ease of Use:** 8.0/10 (Category avg: 8.8/10) - **Ease of Admin:** 8.0/10 (Category avg: 8.5/10) **Who Is the Company Behind Sesame Software?** - **Seller:** [Sesame Software](https://www.g2.com/sellers/sesame-software) - **Company Website:** https://www.sesamesoftware.com - **Year Founded:** 1988 - **HQ Location:** Santa Clara, CA - **Twitter:** @SesameSoft (1 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/413870/ (28 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Information Technology and Services, Insurance - **Company Size:** 61% Enterprise, 37% Mid-Market #### What Are Sesame Software's Pros and Cons? **Pros:** - Customer Support (8 reviews) - Ease of Use (8 reviews) - Integrations (6 reviews) - Data Management (4 reviews) - Easy Setup (4 reviews) **Cons:** - Poor Documentation (4 reviews) - Configuration Issues (2 reviews) - Error Management (2 reviews) - Poor Interface Design (2 reviews) - Technical Issues (2 reviews) ### What Do G2 Reviewers Say About Sesame Software? *AI-generated summary from verified user reviews* **Pros:** - Users highlight the **responsive and knowledgeable customer support** of Sesame Software, ensuring quick issue resolution and reliable usage. - Users love the **ease of use** of Sesame Software, highlighting its intuitive interface and straightforward setup process. - Users value the **seamless integration** capabilities of Sesame Software, enhancing data management efficiency and ease of use. - Users value the **seamless data management** capabilities of Sesame Software, ensuring efficient sync and robust backup solutions. - Users love the **easy setup** of Sesame Software, enjoying its intuitive interface and seamless integration for efficient data management. **Cons:** - Users find the **poor documentation** challenging, especially for troubleshooting and advanced configuration, complicating their experience. - Users face **configuration issues** that can complicate setup and synchronization, requiring careful planning and consideration. - Users find **error management challenging** due to non-intuitive handling and insufficient documentation impacting troubleshooting efforts. - Users find the **poor interface design** of Sesame Software detracts from usability and overall user experience. - Users experience **technical issues** with Sesame Software, particularly when SQL goes down and jobs fail to recover properly. #### What Are Recent G2 Reviews of Sesame Software? **"[Netsuite to SQL Backups - Solid Support](https://www.g2.com/survey_responses/sesame-software-review-12831470)"** **Rating:** 4.5/5.0 stars *— Verified User in Non-Profit Organization Management* [Read full review](https://www.g2.com/survey_responses/sesame-software-review-12831470) --- **"[Exceptional Partner for Legacy ERP Data Archival](https://www.g2.com/survey_responses/sesame-software-review-12590339)"** **Rating:** 5.0/5.0 stars *— Susann E.* [Read full review](https://www.g2.com/survey_responses/sesame-software-review-12590339) --- #### What Are G2 Users Discussing About Sesame Software? - [What is Relational Junction used for?](https://www.g2.com/discussions/what-is-relational-junction-used-for) - 1 comment ### 5. [Adaptris](https://www.g2.com/products/adaptris/reviews) Businesses today align themselves with global partners and having collaborative relationships is critical. Supply chain synchronisation at its core is about looking at inventory and developing relationships with trading partners to enhance visibility and processes, both internally and across the trading partner network. **Average Rating:** 5.0/5.0 **Total Reviews:** 2 **How Do G2 Users Rate Adaptris?** - **Quality of Support:** 10.0/10 (Category avg: 8.9/10) - **Ease of Use:** 10.0/10 (Category avg: 8.8/10) **Who Is the Company Behind Adaptris?** - **Seller:** [Adaptris](https://www.g2.com/sellers/adaptris) - **Year Founded:** 1998 - **HQ Location:** Sutton, GB - **Twitter:** @adaptris (303 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/adaptris/about/ (16 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 50% Enterprise, 50% Small-Business #### What Are Recent G2 Reviews of Adaptris? **"[Review Platform](https://www.g2.com/survey_responses/adaptris-review-5302296)"** **Rating:** 5.0/5.0 stars *— Verified User in Information Technology and Services* [Read full review](https://www.g2.com/survey_responses/adaptris-review-5302296) --- **"[Adaptris review](https://www.g2.com/survey_responses/adaptris-review-5300903)"** **Rating:** 5.0/5.0 stars *— Verified User in Telecommunications* [Read full review](https://www.g2.com/survey_responses/adaptris-review-5300903) --- #### What Are G2 Users Discussing About Adaptris? - [What is Adaptris used for?](https://www.g2.com/discussions/what-is-adaptris-used-for) ### 6. [Anvizent](https://www.g2.com/products/anvizent-anvizent/reviews) Tired of Data Chaos holding back your business? Say hello to Anvizent, the next-gen technology that guarantees the success of your BI and AI project with instantaneous access to integrated, accurate, reliable data. Powered by the highest level of automation in data management, Anvizent comes with a dynamic 'Configurable Guided Interface' that adjusts to ongoing data changes and business needs. Finally get integrated, accurate, reliable data at the speed of business. Anvizent guarantees 100% Data Accuracy - No Mistakes Every Time **Average Rating:** 4.4/5.0 **Total Reviews:** 4 **How Do G2 Users Rate Anvizent?** - **Has the product been a good partner in doing business?:** 8.8/10 (Category avg: 8.9/10) - **Quality of Support:** 9.2/10 (Category avg: 8.9/10) - **Ease of Use:** 8.3/10 (Category avg: 8.8/10) - **Ease of Admin:** 9.2/10 (Category avg: 8.5/10) **Who Is the Company Behind Anvizent?** - **Seller:** [Anvizent](https://www.g2.com/sellers/anvizent) - **Year Founded:** 2017 - **HQ Location:** Alpharetta, US - **LinkedIn® Page:** https://www.linkedin.com/company/anvizent/ (33 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 50% Mid-Market, 50% Small-Business #### What Are Recent G2 Reviews of Anvizent? **"[How Anvizent has changed our Business](https://www.g2.com/survey_responses/anvizent-review-9003617)"** **Rating:** 4.0/5.0 stars *— Duncan R.* [Read full review](https://www.g2.com/survey_responses/anvizent-review-9003617) --- **"[Great team to work with! Powerful tools for data management](https://www.g2.com/survey_responses/anvizent-review-9141063)"** **Rating:** 5.0/5.0 stars *— Shaun B.* [Read full review](https://www.g2.com/survey_responses/anvizent-review-9141063) --- ### 7. [Big Data Governance Edition](https://www.g2.com/products/big-data-governance-edition/reviews) Enable faster, flexible, and repeatable data ingestion and integration on Hadoop. **Average Rating:** 4.3/5.0 **Total Reviews:** 2 **How Do G2 Users Rate Big Data Governance Edition?** - **Quality of Support:** 10.0/10 (Category avg: 8.9/10) - **Ease of Use:** 10.0/10 (Category avg: 8.8/10) **Who Is the Company Behind Big Data Governance Edition?** - **Seller:** [Informatica](https://www.g2.com/sellers/informatica) - **Year Founded:** 1993 - **HQ Location:** Redwood City, CA - **Twitter:** @Informatica (99,643 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/3858/ (2,802 employees on LinkedIn®) - **Ownership:** NYSE: INFA **Who Uses This Product?** - **Company Size:** 100% Mid-Market, 50% Enterprise #### What Are Recent G2 Reviews of Big Data Governance Edition? **"[Good for faster easy data ingestion](https://www.g2.com/survey_responses/big-data-governance-edition-review-5228131)"** **Rating:** 4.0/5.0 stars *— Verified User in Financial Services* [Read full review](https://www.g2.com/survey_responses/big-data-governance-edition-review-5228131) --- **"[Big data governance review](https://www.g2.com/survey_responses/big-data-governance-edition-review-4424959)"** **Rating:** 4.5/5.0 stars *— Kelsey K.* [Read full review](https://www.g2.com/survey_responses/big-data-governance-edition-review-4424959) --- #### What Are G2 Users Discussing About Big Data Governance Edition? - [What is Big Data Governance Edition used for?](https://www.g2.com/discussions/what-is-big-data-governance-edition-used-for) ### 8. [Bruin Data Cloud](https://www.g2.com/products/bruin-data-cloud/reviews) Bruin is an AI-native Customer Data Platform (CDP) that helps teams unify customer data, build a reliable customer 360, and activate insights across marketing, product, support, and analytics workflows. Connect data from your warehouse, applications, databases, and SaaS tools to create a single source of truth for customer behavior. Bruin automatically manages data ingestion, transformation, quality monitoring, and activation, ensuring teams always work with trusted, up-to-date customer data. Bruin's data platform enables data ingestion, data transformation, data quality, observability and governance in a single, unified platform. Using Bruin, teams can ingest data from variety of sources, transform their data in their data warehouse / data lake, introduce data quality checks for end-to-end pipeline health, and monitor their executions including tracking costs, permissions, pipeline run times and more. With Bruin’s AI Data Analyst, business teams can ask questions in plain English and instantly analyze customer segments, campaign performance, retention trends, churn risk, conversion funnels, and lifetime value without writing SQL. Bruin's AI-native features enable AI agents to create, monitor, and maintain pipelines as well as analyze data and build dashboards & reports - the AI Data Analyst and AI Data Engineer seamlessly integrate into Slack, Teams, WhatsApp, etc. **Average Rating:** 4.8/5.0 **Total Reviews:** 2 **How Do G2 Users Rate Bruin Data Cloud?** - **Has the product been a good partner in doing business?:** 10.0/10 (Category avg: 8.9/10) - **Quality of Support:** 10.0/10 (Category avg: 8.9/10) - **Ease of Use:** 8.3/10 (Category avg: 8.8/10) - **Ease of Admin:** 10.0/10 (Category avg: 8.5/10) **Who Is the Company Behind Bruin Data Cloud?** - **Seller:** [Bruin Data Limited](https://www.g2.com/sellers/bruin-data-limited) - **Year Founded:** 2013 - **LinkedIn® Page:** http://www.linkedin.com/company/bruingroupllc (30 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 100% Small-Business #### What Are Recent G2 Reviews of Bruin Data Cloud? **"[Insanely Powerful Data Structuring and Analysis with Built-In Fact Checking](https://www.g2.com/survey_responses/bruin-data-cloud-review-12637773)"** **Rating:** 5.0/5.0 stars *— Verified User in Computer Software* [Read full review](https://www.g2.com/survey_responses/bruin-data-cloud-review-12637773) --- **"[Fantastic tool, adapting rapidly to the needs of the market.](https://www.g2.com/survey_responses/bruin-data-cloud-review-12632175)"** **Rating:** 4.5/5.0 stars *— Sana B.* [Read full review](https://www.g2.com/survey_responses/bruin-data-cloud-review-12632175) --- ### 9. [DataEdge](https://www.g2.com/products/securekloud-technologies-dataedge/reviews) SecureKloud’s DataEdge platform offers highly modular, scalable, and API-driven solutions to enable AI engineering and data analytics for deriving meaningful insights out of your datasets. **Average Rating:** 4.5/5.0 **Total Reviews:** 2 **How Do G2 Users Rate DataEdge?** - **Quality of Support:** 9.2/10 (Category avg: 8.9/10) - **Ease of Use:** 9.2/10 (Category avg: 8.8/10) **Who Is the Company Behind DataEdge?** - **Seller:** [SecureKloud Technologies](https://www.g2.com/sellers/securekloud-technologies) - **Year Founded:** 2008 - **HQ Location:** Chennai, IN - **LinkedIn® Page:** https://www.linkedin.com/company/securekloud-technologies/ (253 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 100% Mid-Market #### What Are Recent G2 Reviews of DataEdge? **"[Build Dashboards, Run Queries, And Evaluate At A Place](https://www.g2.com/survey_responses/dataedge-review-9082183)"** **Rating:** 4.5/5.0 stars *— Urvashi G.* [Read full review](https://www.g2.com/survey_responses/dataedge-review-9082183) --- **"[Best Analytical cloud based solution for your business growth](https://www.g2.com/survey_responses/dataedge-review-8728416)"** **Rating:** 4.5/5.0 stars *— Priyanka C.* [Read full review](https://www.g2.com/survey_responses/dataedge-review-8728416) --- ### 10. [Flow Software](https://www.g2.com/products/flow-software/reviews) Statelake is Flow Software’s highly scalable, future-focused integration platform. Built with modern business and technology needs in mind, Statelake takes care of your integrations, so you can focus on growing and scaling your business sustainably. **Average Rating:** 4.5/5.0 **Total Reviews:** 2 **How Do G2 Users Rate Flow Software?** - **Quality of Support:** 10.0/10 (Category avg: 8.9/10) - **Ease of Use:** 8.3/10 (Category avg: 8.8/10) **Who Is the Company Behind Flow Software?** - **Seller:** [Flow Software](https://www.g2.com/sellers/flow-software-b69ee563-2470-4839-bbde-7e2b077633e2) - **Year Founded:** 2005 - **HQ Location:** North Shore City, NZ - **LinkedIn® Page:** https://www.linkedin.com/company/flow-software-limited (39 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 50% Mid-Market, 50% Small-Business #### What Are Recent G2 Reviews of Flow Software? **"[Great effective product at great price](https://www.g2.com/survey_responses/flow-software-review-7600867)"** **Rating:** 4.5/5.0 stars *— Verified User in Computer Software* [Read full review](https://www.g2.com/survey_responses/flow-software-review-7600867) --- **"[An excellent collaborative tool.](https://www.g2.com/survey_responses/flow-software-review-2359792)"** **Rating:** 4.5/5.0 stars *— malaika k.* [Read full review](https://www.g2.com/survey_responses/flow-software-review-2359792) --- #### What Are G2 Users Discussing About Flow Software? - [What is Flow Software used for?](https://www.g2.com/discussions/what-is-flow-software-used-for) ### 11. [Magic xpi Integration Platform](https://www.g2.com/products/magic-xpi-integration-platform/reviews) One platform for dynamic, limitless connectivity A code-free, low maintenance approach - Magic xpi integrates all of your business systems on the cloud, on-premises or in hybrid deployments so your company can maximize its opportunities. With 100+ pre-built and certified connectors, you’ll be able to easily connect apps, databases, APIs, platforms and more in the cloud and on-premise, maximizing the potential of your third-party technologies and delivering a 360° view of your business. Learn more: https://www.magicsoftware.com/integration-platform/xpi/ **Average Rating:** 4.2/5.0 **Total Reviews:** 3 **How Do G2 Users Rate Magic xpi Integration Platform?** - **Has the product been a good partner in doing business?:** 6.7/10 (Category avg: 8.9/10) - **Quality of Support:** 8.3/10 (Category avg: 8.9/10) - **Ease of Use:** 10.0/10 (Category avg: 8.8/10) - **Ease of Admin:** 6.7/10 (Category avg: 8.5/10) **Who Is the Company Behind Magic xpi Integration Platform?** - **Seller:** [Magic Software](https://www.g2.com/sellers/magic-software) - **Year Founded:** 1983 - **HQ Location:** Irvine, California, United States - **Twitter:** @MagicSoftware (7,257 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/magic-software-enterprises/ (490 employees on LinkedIn®) - **Ownership:** NASDAQ: MGIC **Who Uses This Product?** - **Company Size:** 33% Enterprise, 33% Mid-Market #### What Are Recent G2 Reviews of Magic xpi Integration Platform? **"[Middleware Capabilities](https://www.g2.com/survey_responses/magic-xpi-integration-platform-review-8490875)"** **Rating:** 4.0/5.0 stars *— Verified User in Consulting* [Read full review](https://www.g2.com/survey_responses/magic-xpi-integration-platform-review-8490875) --- **"[Great application for interfaces within different systems](https://www.g2.com/survey_responses/magic-xpi-integration-platform-review-1558509)"** **Rating:** 4.5/5.0 stars *— Guillermo V.* [Read full review](https://www.g2.com/survey_responses/magic-xpi-integration-platform-review-1558509) --- #### What Are G2 Users Discussing About Magic xpi Integration Platform? - [What is Magic xpi Integration Platform used for?](https://www.g2.com/discussions/what-is-magic-xpi-integration-platform-used-for) ### 12. [Rapidi](https://www.g2.com/products/rapidi/reviews) Rapidi is a no-code data integration platform that connects enterprise resource planning (ERP) and customer relationship management (CRM) systems, enabling organizations to synchronize and manage business data across different software environments. It is designed for IT teams, operations professionals, and businesses that need to automate data exchange between CRM systems such as Microsoft Dynamics 365 Sales, Salesforce, and HubSpot, as well as ERP systems such as Microsoft Dynamics Business Central, Finance, NAV, and AX, and other APIs and databases. The platform solves the challenge of disconnected business systems, which often result in duplicate data entry, inconsistent information, and a lack of real-time visibility across sales, operations, and finance. RAPIDI automates the flow of critical business data such as customer records, sales orders, invoices, and inventory between ERP and CRM systems. This improves data accuracy, reduces manual work, and supports faster and more informed decision-making. Key features and benefits of Rapidi include: Broad Integration Support: Connects leading ERP and CRM systems, with a strong focus on Microsoft Dynamics and Salesforce, as well as other business applications, APIs, and databases. Flexible Deployment: Supports both cloud and hybrid environments, allowing organizations to align integration setups with their technical and security requirements. Automated Data Synchronization: Schedules and runs data transfers automatically to ensure information remains consistent and up to date across connected systems. No-Code Platform: Enables users to configure and manage integrations without custom development, reducing reliance on technical resources and shortening implementation time. Global Availability and Support: Provides remote implementation and support across multiple time zones, helping reduce operational overhead and deployment costs. Typical use cases for Rapidi include automating ERP sales order creation from CRM opportunities or quotes, synchronizing customer and sales data between ERP and CRM systems, and enabling real-time updates for service and finance teams. It is also used to support system migrations from legacy platforms to modern ERP and CRM environments. Rapidi is suitable for organizations that require reliable ERP–CRM integration to streamline operations, improve data quality, and maintain consistent information across business systems. **Average Rating:** 4.8/5.0 **Total Reviews:** 5 **How Do G2 Users Rate Rapidi?** - **Has the product been a good partner in doing business?:** 10.0/10 (Category avg: 8.9/10) - **Quality of Support:** 9.4/10 (Category avg: 8.9/10) - **Ease of Use:** 9.0/10 (Category avg: 8.8/10) - **Ease of Admin:** 9.2/10 (Category avg: 8.5/10) **Who Is the Company Behind Rapidi?** - **Seller:** [Rapidi](https://www.g2.com/sellers/rapidi) - **Year Founded:** 1992 - **HQ Location:** La Massana, AD - **Twitter:** @rapidionline (261 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/rapidionline (9 employees on LinkedIn®) - **Ownership:** Private **Who Uses This Product?** - **Company Size:** 80% Mid-Market, 20% Small-Business #### What Are Rapidi's Pros and Cons? **Pros:** - Connectivity (2 reviews) - Customer Support (2 reviews) - Data Integration (2 reviews) - Efficiency (2 reviews) - Implementation Ease (2 reviews) **Cons:** - Migration Issues (2 reviews) - Access Management (1 reviews) - Data Limitations (1 reviews) - Lack of Integrations (1 reviews) - Learning Curve (1 reviews) ### What Do G2 Reviewers Say About Rapidi? *AI-generated summary from verified user reviews* **Pros:** - Users highlight the **superb connectivity** of Rapidi, praising its seamless integration and responsive support for various systems. - Users commend Rapidi for its **exceptional customer support** , ensuring seamless integration and efficient operations over the years. - Users praise Rapidi for its **no-code integration setup** , ensuring seamless connectivity and efficient data management across systems. - Users value the **fast implementation** and efficiency of Rapidi, enhancing integration and reducing manual tasks. - Users commend Rapidi for its **fast implementation** , making integration quick and hassle-free for businesses. **Cons:** - Users face **migration issues** , including vendor lock-in and scalability limits with complex data workloads on Rapidi. - Users face challenges with **initial time commitment for training** to maintain data integrity and avoid sync disruptions. - Users experience **data limitations** with Rapidi, facing challenges in scalability and flexibility for complex workloads. - Users experience a **lack of integrations** which restricts flexibility and complicates working with complex data setups. - Users note a significant **learning curve** due to initial time commitments and training for data integrity maintenance. #### What Are Recent G2 Reviews of Rapidi? **"[Easy, nocode integration platform](https://www.g2.com/survey_responses/rapidi-review-12363554)"** **Rating:** 4.0/5.0 stars *— Verified User in Events Services* [Read full review](https://www.g2.com/survey_responses/rapidi-review-12363554) --- **"[Fast, Secure No‑Code HubSpot↔Microsoft Dynamics Sync with Prebuilt Connectors](https://www.g2.com/survey_responses/rapidi-review-12356185)"** **Rating:** 5.0/5.0 stars *— Verified User in Wholesale* [Read full review](https://www.g2.com/survey_responses/rapidi-review-12356185) --- ### 13. [Apache Gobblin](https://www.g2.com/products/apache-gobblin/reviews) Apache Gobblin is a distributed data integration framework designed to simplify common aspects of big data integration such as data ingestion, replication, organization and lifecycle management for both streaming and batch data ecosystems. **Average Rating:** 5.0/5.0 **Total Reviews:** 1 **How Do G2 Users Rate Apache Gobblin?** - **Quality of Support:** 10.0/10 (Category avg: 8.9/10) - **Ease of Use:** 10.0/10 (Category avg: 8.8/10) **Who Is the Company Behind Apache Gobblin?** - **Seller:** [The Apache Software Foundation](https://www.g2.com/sellers/the-apache-software-foundation) - **Year Founded:** 1999 - **HQ Location:** Wakefield, MA - **Twitter:** @TheASF (66,168 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/215982/ (2,470 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 100% Mid-Market #### What Are Recent G2 Reviews of Apache Gobblin? **"[Gobbling the big data.](https://www.g2.com/survey_responses/apache-gobblin-review-892149)"** **Rating:** 5.0/5.0 stars *— Verified User in Information Technology and Services* [Read full review](https://www.g2.com/survey_responses/apache-gobblin-review-892149) --- #### What Are G2 Users Discussing About Apache Gobblin? - [What is Apache Gobblin used for?](https://www.g2.com/discussions/what-is-apache-gobblin-used-for) ### 14. [Black Tiger Platform](https://www.g2.com/products/black-tiger-platform/reviews) AI-powered platform solving data quality, governance, and compliance—in real-time and at scale. **Average Rating:** 4.5/5.0 **Total Reviews:** 1 **How Do G2 Users Rate Black Tiger Platform?** - **Quality of Support:** 8.3/10 (Category avg: 8.9/10) - **Ease of Use:** 6.7/10 (Category avg: 8.8/10) **Who Is the Company Behind Black Tiger Platform?** - **Seller:** [Black Tiger](https://www.g2.com/sellers/black-tiger) - **Year Founded:** 2015 - **HQ Location:** New York, US - **LinkedIn® Page:** https://www.linkedin.com/company/blacktigertech/ (159 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 50% Enterprise, 50% Mid-Market #### What Are Black Tiger Platform's Pros and Cons? **Pros:** - Compliance Management (1 reviews) - Customer Support (1 reviews) - Data Quality (1 reviews) ### What Do G2 Reviewers Say About Black Tiger Platform? *AI-generated summary from verified user reviews* **Pros:** - Users value the **effective compliance management** of Black Tiger Platform, facilitating GDPR adherence and addressing data challenges. - Users praise the **exceptional customer support** of Black Tiger, ensuring effective communication and understanding of their needs. - Users value the **data quality** of Black Tiger Platform, effectively addressing their challenges and ensuring GDPR compliance. #### What Are Recent G2 Reviews of Black Tiger Platform? **"[Great and efficent Data Platform](https://www.g2.com/survey_responses/black-tiger-platform-review-4604089)"** **Rating:** 5.0/5.0 stars *— Bruno D.* [Read full review](https://www.g2.com/survey_responses/black-tiger-platform-review-4604089) --- **"[Strong partner for data related topics](https://www.g2.com/survey_responses/black-tiger-platform-review-11044046)"** **Rating:** 4.5/5.0 stars *— Rafael B.* [Read full review](https://www.g2.com/survey_responses/black-tiger-platform-review-11044046) --- #### What Are G2 Users Discussing About Black Tiger Platform? - [What is Black Tiger Platform used for?](https://www.g2.com/discussions/what-is-black-tiger-platform-used-for) ### 15. [Blast](https://www.g2.com/products/datablast-blast/reviews) A data platform that bundles critical data functionalities including data orchestration, quality checks, comprehensive documentation, and observability. This platform empowers users to efficiently extract, transform, and interpret data from various sources. It enables the orchestration of these processes with customizable frequency, ensuring data integrity and complete control over the data journey. **Average Rating:** 5.0/5.0 **Total Reviews:** 1 **How Do G2 Users Rate Blast?** - **Quality of Support:** 10.0/10 (Category avg: 8.9/10) - **Ease of Use:** 10.0/10 (Category avg: 8.8/10) **Who Is the Company Behind Blast?** - **Seller:** [Datablast](https://www.g2.com/sellers/datablast) - **Year Founded:** 2021 - **HQ Location:** İstanbul - **Twitter:** @Datablast_io (1 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/datablastcompany (3 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 100% Mid-Market #### What Are Recent G2 Reviews of Blast? **"[Effective, easy to use and great UI.](https://www.g2.com/survey_responses/blast-review-9214982)"** **Rating:** 5.0/5.0 stars *— Cihan B.* [Read full review](https://www.g2.com/survey_responses/blast-review-9214982) --- ### 16. [Dagster](https://www.g2.com/products/dagster/reviews) Ship data pipelines with extraordinary velocity. Dagster is the cloud-native orchestrator for the whole development lifecycle, with integrated lineage and observability, a declarative programming model, and best-in-class testability. **Average Rating:** 4.5/5.0 **Total Reviews:** 2 **How Do G2 Users Rate Dagster?** - **Quality of Support:** 10.0/10 (Category avg: 8.9/10) - **Ease of Use:** 7.5/10 (Category avg: 8.8/10) **Who Is the Company Behind Dagster?** - **Seller:** [Dagster Labs](https://www.g2.com/sellers/dagster-labs) - **Year Founded:** 2018 - **HQ Location:** San Francisco ,California ,United States - **LinkedIn® Page:** https://www.linkedin.com/company/dagsterlabs/ (92 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 50% Mid-Market, 50% Small-Business #### What Are Dagster's Pros and Cons? **Pros:** - Analytics (2 reviews) - Ease of Use (2 reviews) - Features (2 reviews) - Flexibility (2 reviews) - Data Engineering (1 reviews) **Cons:** - Difficult Learning (2 reviews) - Learning Curve (2 reviews) - Learning Difficulty (2 reviews) - Steep Learning Curve (2 reviews) - Complex Setup (1 reviews) ### What Do G2 Reviewers Say About Dagster? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **robust analytics capabilities** of Dagster, highlighting its reliability and transparency in data orchestration. - Users highlight the **ease of use** of Dagster, noting its intuitive design and reduced complexity for data orchestration. - Users value the **asset-centric approach** of Dagster, enhancing reliability and transparency in data orchestration. - Users value the **flexibility** of Dagster, appreciating its asset-centric approach to diverse data engineering use cases. - Users admire the **sophisticated and modern tool** that fits nearly all data engineering use cases effectively. **Cons:** - Users find the **difficult learning** process challenging, complicating initial adoption and hindering usability for smaller teams. - Users find the **steep learning curve** of Dagster challenging, hindering smooth adoption and initial usage. - Users find the **steep learning difficulty** of Dagster challenging, complicating adoption for smaller teams. - Users find Dagster's **steep learning curve** challenging, especially during initial setup and integration into workflows. - Users find the **complex setup** of Dagster challenging, complicating adoption and overwhelming smaller teams. #### What Are Recent G2 Reviews of Dagster? **"[Dagster: Review](https://www.g2.com/survey_responses/dagster-review-12205767)"** **Rating:** 4.0/5.0 stars *— Aarsh B.* [Read full review](https://www.g2.com/survey_responses/dagster-review-12205767) --- **"[Much more advanced and modern alternative to Apache Airflow](https://www.g2.com/survey_responses/dagster-review-11304116)"** **Rating:** 5.0/5.0 stars *— Kelvin Ngoc Nguyen L.* [Read full review](https://www.g2.com/survey_responses/dagster-review-11304116) --- ### 17. [Data Flow Manager](https://www.g2.com/products/data-flow-manager/reviews) Data Flow Manager (DFM) is a purpose-built tool to deploy and promote Apache NiFi data flows within minutes – no need for NiFi UI and controller services, 100% on-premises with zero cloud dependency. Designed for organizations prioritizing data sovereignty, DFM eliminates vendor lock-in and cloud exposure. With a simple pay-per-node model, you can run unlimited NiFi data flows without paying for extra CPUs. DFM automates and accelerates deployment across environments with features like NiFi data flow deployment, scheduling, and promotion in just a few minutes. Role-Based Access Control (RBAC), complete audit logging, and built-in performance analytics give teams control and visibility over their data operations. DFM’s AI-powered NiFi Data Flow Creation Assistant helps teams build better NiFi data flows, faster. Its structure and performance analysis tools ensure your NiFi flows are optimized from the start. Backed by 24x7 NiFi expert support and a 99.99% uptime guarantee, DFM is built for secure, scalable, and always-on NiFi operations. DFM is your all-in-one platform for reliable and efficient NiFi data flow management — no need for NiFi UI & controller services, no cloud, no compromise. Contact: sales@ksolves.com **Average Rating:** 5.0/5.0 **Total Reviews:** 1 **How Do G2 Users Rate Data Flow Manager?** - **Has the product been a good partner in doing business?:** 10.0/10 (Category avg: 8.9/10) - **Quality of Support:** 10.0/10 (Category avg: 8.9/10) - **Ease of Use:** 10.0/10 (Category avg: 8.8/10) - **Ease of Admin:** 10.0/10 (Category avg: 8.5/10) **Who Is the Company Behind Data Flow Manager?** - **Seller:** [Ksolves](https://www.g2.com/sellers/ksolves) - **Year Founded:** 2012 - **HQ Location:** Noida, IN - **Twitter:** @_Ksolves (902 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/ksolves/ (881 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 100% Enterprise #### What Are Data Flow Manager's Pros and Cons? **Pros:** - Ease of Use (1 reviews) - Flexibility (1 reviews) - Performance (1 reviews) - Problem Solving (1 reviews) - Time Management (1 reviews) **Cons:** - Feature Limitations (1 reviews) ### What Do G2 Reviewers Say About Data Flow Manager? *AI-generated summary from verified user reviews* **Pros:** - Users find Data Flow Manager to be **incredibly easy to use** , streamlining complex data operations effortlessly from one portal. - Users value the **flexibility** of Data Flow Manager, enabling efficient management of real-time data across various environments. - Users value the **exceptional performance** of Data Flow Manager, enhancing efficiency and confidence in managing data at scale. - Users value the **problem-solving capabilities** of Data Flow Manager, streamlining data operations and enhancing deployment efficiency. - Users value the **time-saving capabilities** of Data Flow Manager, enhancing efficiency in managing large-scale data operations. **Cons:** - Users suggest that **feature limitations** in Data Flow Manager restrict broader integration with other essential tools and platforms. #### What Are Recent G2 Reviews of Data Flow Manager? **"[A Game-Changer for managing and deploying NiFi and NiFi DataFlows](https://www.g2.com/survey_responses/data-flow-manager-review-11492779)"** **Rating:** 5.0/5.0 stars *— Verified User in Logistics and Supply Chain* [Read full review](https://www.g2.com/survey_responses/data-flow-manager-review-11492779) --- ### 18. [Lingk Cloud Data Integration Platform](https://www.g2.com/products/lingk-cloud-data-integration-platform/reviews) Lingk is the industry’s first iPaaS+ platform with autonomous Agents. The All-in-One Platform offers everything you need to unify, automate, and manage your data for the Agentic Enterprise. Combining an enterprise no-code integration platform, a metadata-first, zero-copy Data Cloud, and the Data Integrator Agent, Lingk empowers organizations to achieve faster, smarter data workflows across on-prem and multi-cloud environments. Build an Agent-ready data fabric and optimize business process automations with Lingk. **Average Rating:** 5.0/5.0 **Total Reviews:** 1 **Who Is the Company Behind Lingk Cloud Data Integration Platform?** - **Seller:** [Lingk](https://www.g2.com/sellers/lingk) - **Year Founded:** 2015 - **HQ Location:** San Francisco, US - **LinkedIn® Page:** https://www.linkedin.com/company/lingk/ (15 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 100% Mid-Market #### What Are Recent G2 Reviews of Lingk Cloud Data Integration Platform? **"[Success through Support of Lingk with Salesforce Integration](https://www.g2.com/survey_responses/lingk-cloud-data-integration-platform-review-7475657)"** **Rating:** 5.0/5.0 stars *— Kevin Z.* [Read full review](https://www.g2.com/survey_responses/lingk-cloud-data-integration-platform-review-7475657) --- ### 19. [Lore IO](https://www.g2.com/products/lore-io/reviews) Lore IO is a data management platform provider that unifies on-demand, real-time business knowledge. **Average Rating:** 4.5/5.0 **Total Reviews:** 1 **How Do G2 Users Rate Lore IO?** - **Quality of Support:** 10.0/10 (Category avg: 8.9/10) - **Ease of Use:** 8.3/10 (Category avg: 8.8/10) **Who Is the Company Behind Lore IO?** - **Seller:** [Lore IO](https://www.g2.com/sellers/lore-io) - **Year Founded:** 1997 - **HQ Location:** Irvine, California, United States - **Twitter:** @teamLoreIO (26 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/alteryx/ (2,323 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 100% Enterprise #### What Are Recent G2 Reviews of Lore IO? **"[Lore IO is a no code AI driven platform which can help you integrate data with minimal efforts.](https://www.g2.com/survey_responses/lore-io-review-6966983)"** **Rating:** 4.5/5.0 stars *— Rohit A.* [Read full review](https://www.g2.com/survey_responses/lore-io-review-6966983) --- ### 20. [Oracle Event Hub Cloud Service](https://www.g2.com/products/oracle-event-hub-cloud-service/reviews) Oracle Event Hub Cloud Service delivers the power of Kafka as a managed streaming data platform integrated into the Oracle Cloud ecosystem. Create Topics and start streaming or manage and deploy your own Dedicated Kafka Cluster with Elastic Scalability. **Average Rating:** 4.5/5.0 **Total Reviews:** 1 **Who Is the Company Behind Oracle Event Hub Cloud Service?** - **Seller:** [Oracle](https://www.g2.com/sellers/oracle) - **Year Founded:** 1977 - **HQ Location:** Austin, TX - **Twitter:** @Oracle (827,997 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/1028/ (208,078 employees on LinkedIn®) - **Ownership:** NYSE:ORCL **Who Uses This Product?** - **Company Size:** 50% Enterprise, 50% Mid-Market #### What Are Recent G2 Reviews of Oracle Event Hub Cloud Service? **"[User friendly. Adaptable ](https://www.g2.com/survey_responses/oracle-event-hub-cloud-service-review-1265305)"** **Rating:** 4.5/5.0 stars *— Verified User in Consumer Services* [Read full review](https://www.g2.com/survey_responses/oracle-event-hub-cloud-service-review-1265305) --- ### 21. [Palantir HyperAuto](https://www.g2.com/products/palantir-hyperauto/reviews) HyperAuto is an out-of-the-box tool that automatically transforms ERP and CRM data into clean, intelligible tables and a human-centric semantic layer. Utilizing metadata, the data pipelines are generated dynamically, without the need to write any code, and can keep pace with changes in the structure of the source systems. The cleaned data can then be exported incrementally to an existing data lake / warehouse. With a common language amongst the data, a customer can use a tool to analyze the data and make key business decisions. Unlike a common ETL tool, HyperAuto also has first-class functionality for writing back to ERP and CRM systems, that makes the underlying data sets more valuable over time, saving time, resource allocation, and effort, while providing you the most accurate, and real-time data for decision making. This is coupled with Palantir's best-in-class data security and governance. **Average Rating:** 4.5/5.0 **Total Reviews:** 1 **How Do G2 Users Rate Palantir HyperAuto?** - **Quality of Support:** 10.0/10 (Category avg: 8.9/10) - **Ease of Use:** 10.0/10 (Category avg: 8.8/10) **Who Is the Company Behind Palantir HyperAuto?** - **Seller:** [Palantir](https://www.g2.com/sellers/palantir) - **HQ Location:** Denver, US - **Twitter:** @PalantirTech (425,595 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/palantir-technologies/ (5,858 employees on LinkedIn®) - **Ownership:** PLTR (NYSE) **Who Uses This Product?** - **Company Size:** 100% Mid-Market #### What Are Recent G2 Reviews of Palantir HyperAuto? **"[Manage Every Data Work Efficiently With Palantir HyperAuto](https://www.g2.com/survey_responses/palantir-hyperauto-review-8603510)"** **Rating:** 4.5/5.0 stars *— Amruta k.* [Read full review](https://www.g2.com/survey_responses/palantir-hyperauto-review-8603510) --- ### 22. [Popsink](https://www.g2.com/products/popsink/reviews) Popsink serves as a foundational platform for seamless data movement. Its cutting-edge connectors enables automated, real-time, and continuous data replication across databases, systems, applications, and more. With live connections built in minutes and easily extensible, Popsink automatically scales to evolving data needs and integrates with new services with ease. Businesses rely on Popsink for data platform ingestion, cloud migration projects, CRM enrichment, real-time analytics, and a wide range of other use cases. **Average Rating:** 4.0/5.0 **Total Reviews:** 1 **How Do G2 Users Rate Popsink?** - **Has the product been a good partner in doing business?:** 8.3/10 (Category avg: 8.9/10) - **Quality of Support:** 8.3/10 (Category avg: 8.9/10) - **Ease of Use:** 8.3/10 (Category avg: 8.8/10) - **Ease of Admin:** 6.7/10 (Category avg: 8.5/10) **Who Is the Company Behind Popsink?** - **Seller:** [Popsink](https://www.g2.com/sellers/popsink) - **Year Founded:** 2021 - **HQ Location:** Paris, FR - **LinkedIn® Page:** https://www.linkedin.com/company/popsink (7 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 100% Mid-Market #### What Are Popsink's Pros and Cons? **Pros:** - Connectivity (1 reviews) - Connectors (1 reviews) - Connectors Quantity (1 reviews) - Customer Support (1 reviews) - Data Management (1 reviews) ### What Do G2 Reviewers Say About Popsink? *AI-generated summary from verified user reviews* **Pros:** - Users praise the **easy connectivity** of Popsink, efficiently managing multiple data feeds with minimal effort. - Users value the **easy management of connectors and pipelines** , enhancing integration versatility with minimal effort. - Users value the **abundant connectors** in Popsink, enabling effortless management of multiple data feeds. - Users appreciate the **helpful customer support** from the PopSink team, making initial project challenges easier to manage. - Users value the **easy data management** features of Popsink, appreciating straightforward connector and pipeline handling. #### What Are Recent G2 Reviews of Popsink? **"[Great solution to stream data from and to different systems](https://www.g2.com/survey_responses/popsink-review-10785821)"** **Rating:** 4.0/5.0 stars *— Antoine L.* [Read full review](https://www.g2.com/survey_responses/popsink-review-10785821) --- ### 23. [Rudol](https://www.g2.com/products/rudol-rudol/reviews) Unlock the real power of your Data In today's data-driven landscape, the quality of your data is paramount. Poor data quality can lead to wrong business decisions, poor quality software or biased AI trainings, due to inaccurate, incomplete, or unreliable information. Enter Rudol, your data quality partner, designed to elevate your data quality game to new heights. Rudol is a comprehensive data quality platform that empowers organizations to maximize the value of their data. It's tailor-made for enterprises that recognize the importance of data quality, from improving decision-making to regulatory compliance, machine learning training or simply reducing problems in published software. And it does it for your whole organization, because it requires no technical background or coding skills whatsoever, its completely self service with 24/7 support, and all user accounts are Free, because the subscription cost is determined by the volume of your Data, enabling your whole structure to be part of the process. The foundation of data quality is understanding the landscape of your Assets. Rudol's Data Catalog allows organizations to bring order to their stack, by adding data sources from the most popular technologies, whether it's structured SQL databases, spreadsheets, dashboards, or even streaming sources. Then teams can perform Governance processes and define Owners, classify under Domains or Tags, put sensitive labels and help teams discover unknown sources for their projects. For those who don't want to have another browser tab opened, Rudol provides Slack, Microsoft Teams and Google Chrome plugins with vast functionalities, so you can find and share resources while chatting with another team member, or in your browser as a sidebar, while using your favorite analytics platform. Enabling Data Quality is a tedious process, Business Stakeholders have to chime in trying to translate their vision into technical requirements, and Software Engineers have to interpret those requirements, for coding boring, repetitive and time consuming scripts. This process is done with friction, and is very difficult to maintain over time, so Rudol bypasses this process by giving Business Stakeholders easy to build Validations that require no coding background and are extremely easy to configure. Choose from more than 15 Business Rules Validations or let Rudol parse your Data to pre configure some of them, the process takes less than 3 minutes and you can massively configure Validations to all your Assets in an instant. Releasing your Data Team from this repetitive tasks is crucial for optimizing their work and getting more value out of the practice, that's why Rudol also offers AI Validations to detect Anomalies where no business rules are defined. Use one of our 3 models to detect inconsistencies where not even Business Stakeholders can notice, and proactively notify your interested roles to identify hidden problems or false positives, because the models learn and improve with your feedback. Rudol also offers Lineage level traceability for Root Cause and Impact Analysis, allowing you to trace data from source to destination across data pipelines. Understand the upstream and downstream implications of any data issue, promoting accountability and transparency, or copy Validations accross your pipeline flow for higher quality coverage. With Rudol, Data Quality becomes accesible and easy to execute. It's designed for all levels of technical expertise, allowing everyone in your organization to participate in maintaining data quality. Rudol enhances decision-making, reduces infrastructure costs, and empowers organizations to make the most out of their data. Don't let poor data quality hinder your success. Choose Rudol and enable the real power of your Data. **Average Rating:** 5.0/5.0 **Total Reviews:** 1 **Who Is the Company Behind Rudol?** - **Seller:** [Rudol](https://www.g2.com/sellers/rudol) - **Year Founded:** 2022 - **HQ Location:** N/A - **LinkedIn® Page:** https://www.linkedin.com/company/rudol (7 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 100% Small-Business #### What Are Recent G2 Reviews of Rudol? **"[Game-changer enhancing our data processes.](https://www.g2.com/survey_responses/rudol-review-8560068)"** **Rating:** 5.0/5.0 stars *— Diego G.* [Read full review](https://www.g2.com/survey_responses/rudol-review-8560068) --- ### 24. [SyncSort Integrate](https://www.g2.com/products/syncsort-integrate/reviews) Trillium Refine enables you to anticipate opportunities. **Average Rating:** 5.0/5.0 **Total Reviews:** 1 **How Do G2 Users Rate SyncSort Integrate?** - **Quality of Support:** 10.0/10 (Category avg: 8.9/10) - **Ease of Use:** 10.0/10 (Category avg: 8.8/10) **Who Is the Company Behind SyncSort Integrate?** - **Seller:** [Precisely](https://www.g2.com/sellers/precisely-0b25c016-ffa5-4f51-9d9e-fcbc9f54cc55) - **HQ Location:** Burlington, Massachusetts - **Twitter:** @PreciselyData (3,963 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/64863146/ (3,006 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 100% Mid-Market #### What Are Recent G2 Reviews of SyncSort Integrate? **"[SyncSort - "Managing Data"](https://www.g2.com/survey_responses/syncsort-integrate-review-9875608)"** **Rating:** 5.0/5.0 stars *— Ujjwal S.* [Read full review](https://www.g2.com/survey_responses/syncsort-integrate-review-9875608) --- ### 25. [The Cognite AI & Data Platform](https://www.g2.com/products/the-cognite-ai-data-platform/reviews) The Cognite AI and Data Platform™ is a sophisticated Industrial DataOps solution specifically designed for asset-intensive industries seeking to harness the power of their operational and engineering data. Founded in 2016 and based in Tempe, Arizona, Cognite aims to facilitate the transformation of complex data environments into actionable insights that drive efficiency and innovation across various sectors. This cloud-native platform excels in ingesting and contextualizing data from a multitude of sources, including Information Technology (IT), Operational Technology (OT), and engineering systems. By creating a unified industrial knowledge graph, the Cognite AI and Data Platform integrates data from historians, Enterprise Resource Planning (ERP) systems, Computerized Maintenance Management Systems (CMMS), and even 3D models. This comprehensive approach allows organizations to standardize their data models and utilize robust APIs, enabling secure workspaces that support advanced analytics, interactive dashboards, and AI-driven applications. Targeted primarily at industries that rely heavily on operational data, such as manufacturing, energy, and utilities, the Cognite AI and Data Platform addresses specific use cases that enhance productivity and operational efficiency. For instance, organizations can leverage the platform for production optimization, where real-time data insights lead to improved throughput and reduced operational bottlenecks. Additionally, the platform supports predictive maintenance initiatives, allowing companies to anticipate equipment failures before they occur, thereby minimizing downtime and associated costs. Key features of the Cognite AI and Data Platform include its ability to transform fragmented data into a trusted and contextual foundation, which is crucial for making informed decisions. By providing a centralized repository of data, users gain full ownership and control over their information, facilitating compliance and security. Moreover, the platform’s scalability enables organizations to implement AI initiatives that can evolve with their operational needs, ensuring that they remain competitive in a rapidly changing industrial landscape. Overall, the Cognite AI and Data Platform stands out in the DataOps category by offering a comprehensive solution that not only integrates disparate data sources but also empowers organizations to unlock the full potential of their industrial data. Through its focus on contextualization and user-friendly interfaces, it provides significant value to companies looking to enhance their operational capabilities and drive long-term growth. **Average Rating:** 4.8/5.0 **Total Reviews:** 3 **How Do G2 Users Rate The Cognite AI & Data Platform?** - **Quality of Support:** 9.2/10 (Category avg: 8.9/10) - **Ease of Use:** 5.8/10 (Category avg: 8.8/10) **Who Is the Company Behind The Cognite AI & Data Platform?** - **Seller:** [Cognite](https://www.g2.com/sellers/cognite) - **Company Website:** https://www.cognite.com/en/ - **Year Founded:** 2016 - **HQ Location:** Tempe, Arizona, United States - **LinkedIn® Page:** https://www.linkedin.com/company/cognitedata (760 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 100% Enterprise #### What Are Recent G2 Reviews of The Cognite AI & Data Platform? **"[Empowers Data Contextualization with Ease and Trust](https://www.g2.com/survey_responses/the-cognite-ai-data-platform-review-12948927)"** **Rating:** 5.0/5.0 stars *— Jeremy K.* [Read full review](https://www.g2.com/survey_responses/the-cognite-ai-data-platform-review-12948927) --- **"[Connects Nearly Any Industrial Data Source into a Common Source of Truth](https://www.g2.com/survey_responses/the-cognite-ai-data-platform-review-12951453)"** **Rating:** 5.0/5.0 stars *— Adam G.* [Read full review](https://www.g2.com/survey_responses/the-cognite-ai-data-platform-review-12951453) --- ## What Is Big Data Integration Platforms? [Cloud Data Integration Software](https://www.g2.com/categories/cloud-data-integration) ## What Software Categories Are Similar to Big Data Integration Platforms? - [On-Premise Data Integration Software](https://www.g2.com/categories/on-premise-data-integration) - [Big Data Processing And Distribution Systems](https://www.g2.com/categories/big-data-processing-and-distribution) - [ETL Tools](https://www.g2.com/categories/etl-tools) - [iPaaS Software](https://www.g2.com/categories/ipaas) - [Data Extraction Tools](https://www.g2.com/categories/data-extraction-tools) - [Data Replication Software](https://www.g2.com/categories/data-replication) - [DataOps Platforms](https://www.g2.com/categories/dataops-platforms) --- ## How Do You Choose the Right Big Data Integration Platforms? ### What You Should Know 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. 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? 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.