# Best Big Data Integration Platforms for Small Business *By [Shalaka Joshi](https://research.g2.com/insights/author/shalaka-joshi)* Products classified in the overall Big Data Integration Platforms category are similar in many regards and help companies of all sizes solve their business problems. However, small business features, pricing, setup, and installation differ from businesses of other sizes, which is why we match buyers to the right Small Business Big Data Integration Platforms to fit their needs. Compare product ratings based on reviews from enterprise users or connect with one of G2's buying advisors to find the right solutions within the Small Business Big Data Integration Platforms category. In addition to qualifying for inclusion in the Big Data Integration Platforms category, to qualify for inclusion in the Small Business Big Data Integration Platforms category, a product must have at least 10 reviews left by a reviewer from a small business. ## How Many Big Data Integration Platforms Products Does G2 Track? **Total Products under this Category:** 130 ## How Does G2 Rank Big Data Integration Platforms Products? **Why You Can Trust G2's Software Rankings:** - 30 Analysts and Data Experts - 9,100+ Authentic Reviews - 130+ Products - Unbiased Rankings G2's software rankings are built on verified user reviews, rigorous moderation, and a consistent research methodology maintained by a team of analysts and data experts. Each product is measured using the same transparent criteria, with no paid placement or vendor influence. While reviews reflect real user experiences, which can be subjective, they offer valuable insight into how software performs in the hands of professionals. Together, these inputs power the G2 Score, a standardized way to compare tools within every category. --- **Sponsored** ### CData Sync Unlike volume-based tools with unpredictable pricing, CData Sync offers a single platform for ETL and reverse ETL, with full deployment flexibility and fixed, scalable pricing—so your costs don’t balloon as your data grows. Connect to 250+ enterprise data sources, including: • Salesforce, Microsoft Dynamics, and SAP • SharePoint, NetSuite, Workday, and QuickBooks • ServiceNow, Xero, Sage Intacct, HubSpot, Marketo, Oracle • …and many more Replicate that data into your preferred destinations, such as: • Snowflake, Databricks, SQL Server, Redshift, OneLake, and others Deploy it your way—on-premises, in your own cloud, or in a private-cloud SaaS model. Getting started is simple: 1. Log in 2. Select your source tables 3.Set your sync interval CData Sync handles the rest, using efficient incremental updates that minimize load on your operational systems. The platform includes: • Point-and-click ETL/ELT/reverse ETL • Change Data Capture (CDC) with no elevated database permissions • Complete data control and custom SQL transformations • dbt integration CData Sync centralizes your automated data flows, giving you full control, faster delivery, and the freedom to scale without hidden fees. Download a 30-day free trial of CData Sync or learn more at: www.cdata.com/sync [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%5Bdisplayable_resource_id%5D=1181&secure%5Bdisplayable_resource_type%5D=Category&secure%5Bmedium%5D=sponsored&secure%5Bplacement_reason%5D=neighbor_category&secure%5Bplacement_resource_ids%5D%5B%5D=1181&secure%5Bprioritized%5D=false&secure%5Bproduct_id%5D=124922&secure%5Bresource_id%5D=1186&secure%5Bresource_type%5D=Category&secure%5Bsource_type%5D=category_page&secure%5Bsource_url%5D=https%3A%2F%2Fwww.g2.com%2Fcategories%2Fbig-data-integration-platforms&secure%5Btoken%5D=2422e07a0290fc29ff2280cac6807be8eff428939b0ad01237aff193e9f85625&secure%5Burl%5D=https%3A%2F%2Fwww.cdata.com%2Fsync%2F%3Futm_source%3Dg2%26utm_medium%3Dsponsored-link%26utm_campaign%3Dsync-clicks-etl-tools&secure%5Burl_type%5D=custom_url) --- ## What Are the Top-Rated Big Data Integration Platforms Products in 2026? ### 1. [Google Cloud BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews) BigQuery is a fully managed, AI-ready data analytics platform that helps you maximize value from your data and is designed to be multi-engine, multi-format, and multi-cloud. Store 10 GiB of data and run up to 1 TiB of queries for free per month. **Average Rating:** 4.5/5.0 **Total Reviews:** 1,157 **How Do G2 Users Rate Google Cloud BigQuery?** - **Has the product been a good partner in doing business?:** 8.6/10 (Category avg: 8.9/10) - **Quality of Support:** 8.3/10 (Category avg: 8.9/10) - **Ease of Use:** 8.7/10 (Category avg: 8.9/10) - **Ease of Admin:** 8.5/10 (Category avg: 8.5/10) **Who Is the Company Behind Google Cloud BigQuery?** - **Seller:** [Google](https://www.g2.com/sellers/google) - **Year Founded:** 1998 - **HQ Location:** Mountain View, CA - **Twitter:** @google (31,911,199 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/1441/ (336,169 employees on LinkedIn®) - **Ownership:** NASDAQ:GOOG **Who Uses This Product?** - **Who Uses This:** Data Engineer, Data Analyst - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 38% Enterprise, 35% Mid-Market #### What Are Google Cloud BigQuery's Pros and Cons? **Pros:** - Ease of Use (156 reviews) - Speed (143 reviews) - Fast Querying (120 reviews) - Integrations (118 reviews) - Query Efficiency (114 reviews) **Cons:** - Expensive (127 reviews) - Query Issues (78 reviews) - Cost Issues (63 reviews) - Cost Management (60 reviews) - Learning Curve (54 reviews) ### 2. [Alteryx](https://www.g2.com/products/alteryx/reviews) Alteryx, through it's Alteryx One platform, helps enterprises transform complex, disconnected data into a clean, AI-ready state. Whether you’re creating financial forecasts, analyzing supplier performance, segmenting customer data, analyzing employee retention, or building competitive AI applications from your proprietary data, Alteryx One makes it easy to cleanse, blend, and analyze data to unlock the unique insights that drive impactful decisions. AI-Guided Analytics Alteryx automates and simplifies every stage of data preparation and analysis, from validation and enrichment to predictive analytics and automated insights. Incorporate generative AI directly into your workflows to streamline complex data tasks and generate insights faster. Unmatched flexibility, whether you prefer code-free workflows, natural language commands, or low-code options, Alteryx adapts to your needs. Trusted. Secure. Enterprise-Ready. Alteryx is trusted by over half of the Global 2000 and 19 of the top 20 global banks. With built-in automation, governance, and security, your workflows can scale and maintain compliance while delivering consistent results. And it doesn’t matter if your systems are on-premises, hybrid, or in the cloud; Alteryx fits effortlessly into your infrastructure. Easy to Use. Deeply Connected. What truly sets Alteryx apart is our focus on efficiency and ease of use for analysts and our active community of 700,000 Alteryx users to support you at every step of your journey. With seamless integration to data everywhere including platforms like Databricks, Snowflake, AWS, Google, SAP, and Salesforce, our platform helps unify siloed data and accelerate getting to insights. Visit Alteryx.com for more information, and to start your free trial. **Average Rating:** 4.6/5.0 **Total Reviews:** 651 **How Do G2 Users Rate Alteryx?** - **Has the product been a good partner in doing business?:** 8.9/10 (Category avg: 8.9/10) - **Quality of Support:** 8.5/10 (Category avg: 8.9/10) - **Ease of Use:** 8.7/10 (Category avg: 8.9/10) - **Ease of Admin:** 8.3/10 (Category avg: 8.5/10) **Who Is the Company Behind Alteryx?** - **Seller:** [Alteryx](https://www.g2.com/sellers/alteryx) - **Company Website:** https://www.alteryx.com - **Year Founded:** 1997 - **HQ Location:** Irvine, CA - **Twitter:** @alteryx (26,195 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/903031/ (2,268 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Data Analyst, Analyst - **Top Industries:** Financial Services, Accounting - **Company Size:** 62% Enterprise, 23% Mid-Market #### What Are Alteryx's Pros and Cons? **Pros:** - Ease of Use (333 reviews) - Automation (148 reviews) - Intuitive (132 reviews) - Easy Learning (102 reviews) - Efficiency (102 reviews) **Cons:** - Expensive (88 reviews) - Learning Curve (80 reviews) - Missing Features (62 reviews) - Learning Difficulty (55 reviews) - Slow Performance (41 reviews) ### 3. [Snowflake](https://www.g2.com/products/snowflake/reviews) Snowflake makes enterprise AI easy, efficient and trusted. Thousands of companies around the globe, including hundreds of the world’s largest, use Snowflake’s AI Data Cloud to share data, build applications, and power their business with AI. The era of enterprise AI is here. Learn more at snowflake.com (NYSE: SNOW). **Average Rating:** 4.6/5.0 **Total Reviews:** 686 **How Do G2 Users Rate Snowflake?** - **Has the product been a good partner in doing business?:** 9.0/10 (Category avg: 8.9/10) - **Quality of Support:** 8.7/10 (Category avg: 8.9/10) - **Ease of Use:** 9.0/10 (Category avg: 8.9/10) - **Ease of Admin:** 8.6/10 (Category avg: 8.5/10) **Who Is the Company Behind Snowflake?** - **Seller:** [Snowflake, Inc.](https://www.g2.com/sellers/snowflake-inc) - **Company Website:** https://www.snowflake.com - **Year Founded:** 2012 - **HQ Location:** San Mateo, CA - **Twitter:** @SnowflakeDB (255 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/snowflake-computing/ (10,857 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Data Engineer, Data Analyst - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 45% Mid-Market, 43% Enterprise #### What Are Snowflake's Pros and Cons? **Pros:** - Ease of Use (89 reviews) - Scalability (68 reviews) - Data Management (67 reviews) - Features (66 reviews) - Integrations (61 reviews) **Cons:** - Expensive (53 reviews) - Cost (36 reviews) - Cost Management (32 reviews) - Learning Curve (25 reviews) - Feature Limitations (21 reviews) ### 4. [Workato](https://www.g2.com/products/workato/reviews) Workato is the #1-rated iPaaS and the leader in Enterprise MCP — the platform enterprises trust to unify integration, automation, and AI in one secure, cloud-native runtime. Trusted by over 12,000 customers including half the Fortune 500, Workato connects every system, process, and data source with 14,000+ pre-built connectors. What sets Workato apart: Enterprise MCP turns proven business processes into governed, agent-ready skills that any AI agent — Claude, ChatGPT, Cursor, or custom-built — can execute safely and predictably. No rip-and-replace required. Whether modernizing legacy integrations or deploying agentic AI at scale, Workato delivers the orchestration, governance, and trust needed in the enterprise. **Average Rating:** 4.7/5.0 **Total Reviews:** 726 **How Do G2 Users Rate Workato?** - **Has the product been a good partner in doing business?:** 9.4/10 (Category avg: 8.9/10) - **Quality of Support:** 9.2/10 (Category avg: 8.9/10) - **Ease of Use:** 8.9/10 (Category avg: 8.9/10) - **Ease of Admin:** 9.0/10 (Category avg: 8.5/10) **Who Is the Company Behind Workato?** - **Seller:** [Workato](https://www.g2.com/sellers/workato) - **Company Website:** https://www.workato.com - **Year Founded:** 2013 - **HQ Location:** Mountain View, California - **Twitter:** @Workato (3,615 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/3675685 (1,348 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Software Engineer, Senior Software Engineer - **Top Industries:** Computer Software, Information Technology and Services - **Company Size:** 43% Mid-Market, 33% Enterprise #### What Are Workato's Pros and Cons? **Pros:** - Ease of Use (366 reviews) - Integrations (245 reviews) - Easy Integrations (232 reviews) - Automation (198 reviews) - Features (195 reviews) **Cons:** - Complexity (83 reviews) - Learning Curve (77 reviews) - Missing Features (77 reviews) - Data Limitations (76 reviews) - Expensive (71 reviews) ### 5. [5X](https://www.g2.com/products/5x/reviews) 5X is an end-to-end data and AI platform. The platform organizes your data regardless of source or format. Whether you have a dedicated data team or not, our platform
transforms fragmented data into actionable insights and apps. The customer feedback we get most often is, "This is self-explanatory," and "It's super easy to use." And that is exactly what our goal was—to create a powerful, all-in-one platform that's incredibly easy to use.  The modern data stack has evolved. It's no longer about stitching together vendors. The next-generation modern data stack is an all-in-one platform that offers speed, simplicity, and decreased cost of ownership. That's exactly what we have created at 5X. Companies use 5X for multiple reasons: 1) Speed & productivity. All-in-one data platforms are incredibly efficient. We've seen companies build use cases on day 1.  Contact us to see if you qualify for a free 48 hour jumpstart! 🚀 2) Decrease your total cost of ownership by 30% compared to building your own platform. This doesn't account the people hours needed to support a platform build 🤯 3) Use our full stack data consultancy for support on data engineering & analytics 👨‍💻 5X was founded in 2020 with presence in the USA, Singapore, UK and India. Our global team is 70+ people strong and rapidly growing. We’ve recently raised our seed round from Flybridge Capital and backed by top founders from companies like Datadog, Preset, Astronomer, Mode, Rudderstack and other prominent angel investors. For more information, visit 5X.co We don't just talk about speed and simplicity; we back it up with proof. Speak to us about our 48-hour jumpstart where we can build an end-to-end use case for you in 48 hours for free. **Average Rating:** 4.9/5.0 **Total Reviews:** 81 **How Do G2 Users Rate 5X?** - **Has the product been a good partner in doing business?:** 9.8/10 (Category avg: 8.9/10) - **Quality of Support:** 9.8/10 (Category avg: 8.9/10) - **Ease of Use:** 9.5/10 (Category avg: 8.9/10) - **Ease of Admin:** 9.6/10 (Category avg: 8.5/10) **Who Is the Company Behind 5X?** - **Seller:** [5X](https://www.g2.com/sellers/5x) - **Year Founded:** 2020 - **HQ Location:** San Francisco - **Twitter:** @DataWith5x (49 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/datawith5x/ (128 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Computer Software, Financial Services - **Company Size:** 56% Mid-Market, 40% Small-Business #### What Are 5X's Pros and Cons? **Pros:** - Ease of Use (28 reviews) - Customer Support (18 reviews) - Features (14 reviews) - Integrations (13 reviews) - Data Integration (10 reviews) **Cons:** - Steep Learning Curve (5 reviews) - Complex Setup (4 reviews) - Feature Limitations (4 reviews) - Learning Curve (4 reviews) - Difficult Setup (3 reviews) ### 6. [dbt](https://www.g2.com/products/dbt/reviews) dbt is a transformation workflow that lets data teams quickly and collaboratively deploy analytics code following software engineering best practices like modularity, portability, CI/CD, and documentation. Now anyone who knows SQL can build production-grade data pipelines. **Average Rating:** 4.7/5.0 **Total Reviews:** 204 **How Do G2 Users Rate dbt?** - **Has the product been a good partner in doing business?:** 8.6/10 (Category avg: 8.9/10) - **Quality of Support:** 8.8/10 (Category avg: 8.9/10) - **Ease of Use:** 9.0/10 (Category avg: 8.9/10) - **Ease of Admin:** 8.5/10 (Category avg: 8.5/10) **Who Is the Company Behind dbt?** - **Seller:** [Fivetran](https://www.g2.com/sellers/fivetran) - **Year Founded:** 2012 - **HQ Location:** Oakland, CA - **Twitter:** @fivetran (5,737 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/fivetran/ (1,738 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Data Engineer, Analytics Engineer - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 56% Mid-Market, 27% Small-Business #### What Are dbt's Pros and Cons? **Pros:** - Ease of Use (38 reviews) - Features (22 reviews) - Automation (19 reviews) - Transformation (17 reviews) - Integrations (15 reviews) **Cons:** - Limited Functionality (14 reviews) - Dependency Issues (12 reviews) - Steep Learning Curve (10 reviews) - Error Handling (9 reviews) - Error Reporting (9 reviews) ### 7. [Skyvia](https://www.g2.com/products/skyvia/reviews) Skyvia is a no-code cloud data integration and data pipeline platform that enables ETL, ELT, Reverse ETL, data migration, one-way and bi-directional data sync, workflow automation, real-time connectivity, and much more. Benefits of Using Skyvia: • Cost efficiency: With affordable, flexible pricing plans for each product, Skyvia suites for businesses of any size. • Ease of Use: Based on extensive customer feedback, ease of use is Skyvia's strongest quality. • Flexibility: Skyvia provides adaptable, no-code integration tools for both basic and advanced business scenarios. • Trust: Skyvia is trusted by thousands of data-driven organizations around the globe. With a vast library of 200+ connectors, Skyvia provides seamless integration among various cloud applications, databases, and data warehouses, including Salesforce, Dynamics CRM, QuickBooks Online, SQL Server, Amazon Redshift, Google BigQuery, and others. **Average Rating:** 4.8/5.0 **Total Reviews:** 317 **How Do G2 Users Rate Skyvia?** - **Has the product been a good partner in doing business?:** 9.3/10 (Category avg: 8.9/10) - **Quality of Support:** 9.3/10 (Category avg: 8.9/10) - **Ease of Use:** 9.3/10 (Category avg: 8.9/10) - **Ease of Admin:** 9.4/10 (Category avg: 8.5/10) **Who Is the Company Behind Skyvia?** - **Seller:** [Devart](https://www.g2.com/sellers/devart) - **Year Founded:** 1997 - **HQ Location:** Wilmington, Delaware, USA - **Twitter:** @DevartSoftware (1,739 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/800325/ (257 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** CEO, CTO - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 52% Small-Business, 41% Mid-Market #### What Are Skyvia's Pros and Cons? **Pros:** - Ease of Use (50 reviews) - Easy Integrations (34 reviews) - Easy Setup (33 reviews) - Setup Ease (31 reviews) - Data Management (27 reviews) **Cons:** - Information Deficiency (8 reviews) - Difficult Setup (7 reviews) - Feature Limitations (7 reviews) - Learning Curve (7 reviews) - Poor Documentation (7 reviews) ### 8. [Amazon Redshift](https://www.g2.com/products/amazon-redshift/reviews) Tens of thousands of customers use Amazon Redshift, a fast, fully managed, petabyte-scale data warehouse service that makes it simple and cost-effective to efficiently analyze all your data using your existing business intelligence tools. It is optimized for datasets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions. **Average Rating:** 4.3/5.0 **Total Reviews:** 368 **How Do G2 Users Rate Amazon Redshift?** - **Has the product been a good partner in doing business?:** 8.7/10 (Category avg: 8.9/10) - **Quality of Support:** 8.5/10 (Category avg: 8.9/10) - **Ease of Use:** 8.7/10 (Category avg: 8.9/10) - **Ease of Admin:** 8.4/10 (Category avg: 8.5/10) **Who Is the Company Behind Amazon Redshift?** - **Seller:** [Amazon Web Services (AWS)](https://www.g2.com/sellers/amazon-web-services-aws-3e93cc28-2e9b-4961-b258-c6ce0feec7dd) - **Year Founded:** 2006 - **HQ Location:** Seattle, WA - **Twitter:** @awscloud (2,227,557 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/amazon-web-services/ (156,424 employees on LinkedIn®) - **Ownership:** NASDAQ: AMZN **Who Uses This Product?** - **Who Uses This:** Data Engineer, Senior Data Engineer - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 40% Enterprise, 39% Mid-Market #### What Are Amazon Redshift's Pros and Cons? **Pros:** - Ease of Use (7 reviews) - Integrations (7 reviews) - Easy Integrations (5 reviews) - Fast Querying (5 reviews) - Scalability (5 reviews) **Cons:** - Complexity (5 reviews) - Feature Limitations (5 reviews) - Software Limitations (5 reviews) - Query Issues (4 reviews) - Query Optimization (4 reviews) ### 9. [Weld](https://www.g2.com/products/weld-weld/reviews) Weld delivers an ultra-fast, secure, and reliable way to move data from all your tools, applications, and databases into cloud data warehouses, such as Snowflake, BigQuery, and Databricks. Deploy data pipelines in minutes with connectors that adapt to schema changes, detect duplicates, self-heal on failure, and run without maintenance, so your data team can focus on insights, not infrastructure. **Average Rating:** 4.8/5.0 **Total Reviews:** 101 **How Do G2 Users Rate Weld?** - **Has the product been a good partner in doing business?:** 9.7/10 (Category avg: 8.9/10) - **Quality of Support:** 9.7/10 (Category avg: 8.9/10) - **Ease of Use:** 8.8/10 (Category avg: 8.9/10) - **Ease of Admin:** 9.1/10 (Category avg: 8.5/10) **Who Is the Company Behind Weld?** - **Seller:** [Weld](https://www.g2.com/sellers/weld-733aad41-2e36-4f42-9349-7d847f41d873) - **Company Website:** https://weld.app/ - **Year Founded:** 2021 - **HQ Location:** Copenhagen, DK - **Twitter:** @WeldHQ (98 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/weldhq/ (97 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** CEO - **Top Industries:** Computer Software, Retail - **Company Size:** 58% Small-Business, 41% Mid-Market #### What Are Weld's Pros and Cons? **Pros:** - Ease of Use (16 reviews) - Customer Support (13 reviews) - Features (12 reviews) - Automation (11 reviews) - Data Integration (9 reviews) **Cons:** - Limited Connectors (8 reviews) - Feature Limitations (6 reviews) - Missing Features (5 reviews) - Limited Integrations (4 reviews) - Connectivity Issues (3 reviews) ### 10. [Elastic Stack](https://www.g2.com/products/elastic-stack/reviews) The Elastic Stack, commonly known as the ELK Stack, is a comprehensive suite of open-source tools designed for ingesting, storing, analyzing, and visualizing data in real-time. It comprises Elasticsearch, Kibana, Beats, and Logstash, enabling users to handle data from any source and in any format efficiently. Key Features and Functionality: - Elasticsearch: A distributed, JSON-based search and analytics engine that allows for rapid storage, search, and analysis of large volumes of data. - Kibana: An extensible user interface that provides powerful visualizations, dashboards, and management tools to interpret and present data effectively. - Beats and Logstash: Data ingestion tools that collect and process data from various sources, transforming and forwarding it to Elasticsearch for indexing. - Integrations: A multitude of pre-built integrations that facilitate seamless data collection and connection with the Elastic Stack, enabling quick insights. Primary Value and User Solutions: The Elastic Stack empowers organizations to harness the full potential of their data by providing a scalable and resilient platform for real-time search and analytics. It addresses challenges such as managing large datasets, ensuring high availability, and delivering relevant search results swiftly. By offering a unified solution for data ingestion, storage, analysis, and visualization, the Elastic Stack enables users to gain actionable insights, enhance operational efficiency, and make informed decisions based on their data. **Average Rating:** 4.5/5.0 **Total Reviews:** 99 **How Do G2 Users Rate Elastic Stack?** - **Has the product been a good partner in doing business?:** 8.5/10 (Category avg: 8.9/10) - **Quality of Support:** 8.2/10 (Category avg: 8.9/10) - **Ease of Use:** 8.0/10 (Category avg: 8.9/10) - **Ease of Admin:** 7.6/10 (Category avg: 8.5/10) **Who Is the Company Behind Elastic Stack?** - **Seller:** [Elastic](https://www.g2.com/sellers/elastic) - **Year Founded:** 2012 - **HQ Location:** San Francisco, CA - **Twitter:** @elastic (64,579 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/814025/ (4,986 employees on LinkedIn®) - **Ownership:** NYSE: ESTC **Who Uses This Product?** - **Who Uses This:** Software Engineer, Senior Software Engineer - **Top Industries:** Computer Software, Information Technology and Services - **Company Size:** 46% Mid-Market, 34% Enterprise #### What Are Elastic Stack's Pros and Cons? **Pros:** - Ease of Use (3 reviews) - Flexibility (3 reviews) - Log Management (3 reviews) - Search Efficiency (3 reviews) - Versatility (3 reviews) **Cons:** - Resource Management (3 reviews) - Complexity Issues (2 reviews) - Expensive (2 reviews) - High Memory Usage (2 reviews) - Learning Curve (2 reviews) ### 11. [Coefficient](https://www.g2.com/products/coefficient/reviews) Coefficient is a new way to work with your company data better, faster, and more accurately without ever leaving your spreadsheet, integrating with the tools you already use. Install the Coefficient Excel or Google Sheets extension and use it in a new or existing sheet in seconds. Once installed, Coefficient lives as a sidebar companion so your company data is only a couple of clicks away at any time. Any data source that you work with is available directly in your Coefficient sidebar – such as Salesforce, HubSpot, Snowflake, NetSuite, QuickBooks, MySQL, and Looker – with the ability to consolidate your data from multiple systems into one spreadsheet. Use Coefficient filters to easily customize your imports to only work with the data you need, keeping your spreadsheets performant. Quickly go back anytime to add more data in the same report. Never rebuild the same analysis twice by keeping your data up to date with scheduled updates. And, use Coefficient alerts to trigger Slack or email messages anytime your spreadsheet updates. Now, you can turn your spreadsheet into the most flexible, powerful monitoring system across all of your company data. Say “goodbye” to manual data workflows and “hello” to connected spreadsheets. **Average Rating:** 4.7/5.0 **Total Reviews:** 183 **How Do G2 Users Rate Coefficient?** - **Has the product been a good partner in doing business?:** 9.0/10 (Category avg: 8.9/10) - **Quality of Support:** 8.9/10 (Category avg: 8.9/10) - **Ease of Use:** 9.2/10 (Category avg: 8.9/10) - **Ease of Admin:** 9.2/10 (Category avg: 8.5/10) **Who Is the Company Behind Coefficient?** - **Seller:** [Coefficient](https://www.g2.com/sellers/coefficient) - **Company Website:** https://coefficient.io/ - **Year Founded:** 2020 - **HQ Location:** Palo Alto, CA - **Twitter:** @coefficient_io (351 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/coefficientworks/ (70 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Computer Software, Information Technology and Services - **Company Size:** 48% Mid-Market, 36% Small-Business #### What Are Coefficient's Pros and Cons? **Pros:** - Ease of Use (72 reviews) - Automation (42 reviews) - Integrations (42 reviews) - Time-saving (36 reviews) - Easy Integrations (31 reviews) **Cons:** - Limited Features (18 reviews) - Feature Limitations (17 reviews) - Limitations (13 reviews) - Missing Features (12 reviews) - Integration Issues (11 reviews) ### 12. [Peliqan](https://www.g2.com/products/peliqan/reviews) Peliqan.io is an all-in-one AI-first data integration and automation platform designed for business teams, scale-ups and consultants. Unlike traditional data tools that demand heavy engineering effort, Peliqan enables both business users and technical teams to connect, manage, and activate their data in one collaborative environment - without requiring a dedicated data engineer. With 250+ built-in connectors, Peliqan connects to databases, SaaS business applications (ERP, CRM, Accounting, HRM/ATS etc.), cloud storage, files and APIs as well as on-prem data sources. New connectors are available on demand within 5 business days. Peliqan offers one-click ELT pipelines to the built-in data warehouse, or you can bring your own data warehouse. Peliqan supports all major data warehouses. Thanks to Peliqan’s Excel add-in, business users and consultants can work with real-time data in Excel. Analysts and power users can use Peliqan’s advanced SQL editor with the support of an AI assistant to transform data and prepare business-ready data sets, which can be used in any BI tool such as Microsoft Power BI, Metabase, Tableau, Qlik, Looker etc. Users can also set up Reverse ETL flows. Developers can go even further with Peliqan’s low-code environment, with a built-in virtual AI Data Engineer, where they can: - Build & Publish interactive data apps - Automate writebacks into source systems - Publish API endpoints for data sharing - Implement custom pipelines - Build out internal AI Agents By empowering business users, analysts, consultants and developers, Peliqan dramatically reduces reliance on IT support and speeds up decision-making. Peliqan is not just an ELT data pipeline tool, it’s a complete solution for data orchestration, automation, and activation. Peliqan also acts as the data foundation for Agentic AI, ensuring that AI agents work with trusted, up-to-date 360° views of customers, products, orders, and more - at the speed of a cloud data warehouse. Peliqan’s data warehouse provides an AI-ready data layer out-of-the-box including: - Automatic vectorizing of structured and non-structured data for RAG (Retrieval-Augmented Generation) - Text-to-SQL - MCP Gateway In today’s landscape, a data warehouse is no longer just for BI - it’s the foundation for both BI and AI. With Peliqan.io, organizations can integrate, analyze, and activate their data seamlessly, empowering both humans and AI agents to make smarter, faster decisions. **Average Rating:** 4.8/5.0 **Total Reviews:** 71 **How Do G2 Users Rate Peliqan?** - **Has the product been a good partner in doing business?:** 9.0/10 (Category avg: 8.9/10) - **Quality of Support:** 9.1/10 (Category avg: 8.9/10) - **Ease of Use:** 9.3/10 (Category avg: 8.9/10) - **Ease of Admin:** 8.7/10 (Category avg: 8.5/10) **Who Is the Company Behind Peliqan?** - **Seller:** [Peliqan](https://www.g2.com/sellers/peliqan) - **Company Website:** https://peliqan.io - **Year Founded:** 2022 - **HQ Location:** Gent - **Twitter:** @Peliqan_io (8 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/peliqan-data (27 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Computer Software, Information Technology and Services - **Company Size:** 47% Mid-Market, 42% Small-Business #### What Are Peliqan's Pros and Cons? **Pros:** - Ease of Use (45 reviews) - Integrations (43 reviews) - Easy Integrations (37 reviews) - Connectors (36 reviews) - Data Management (36 reviews) **Cons:** - Learning Difficulty (18 reviews) - Required Technical Skills (12 reviews) - Feature Limitations (10 reviews) - Learning Curve (10 reviews) - Steep Learning Curve (9 reviews) ### 13. [IBM StreamSets](https://www.g2.com/products/ibm-streamsets/reviews) IBM StreamSets is a robust streaming data integration tool for hybrid, multi-cloud environments that enables real-time decision making. It allows ingestion and in-flight transformation of structured, unstructured, and semi-structured data from streaming sources, and reliably delivers trusted data into diverse destinations. Flexible deployment options promote security, cost-effectiveness and performance. With several pre-built connectors, an intuitive no-code/low-code interface, and automatic adaptability to data drifts, StreamSets accelerates data pipeline operationalization. It integrates with IBM’s broader data integration capabilities, enabling reliable pipelines that unify multiple data integration patterns, underpinned by data observability capabilities for continuous data quality monitoring and remediation. That’s why the largest companies in the world trust StreamSets to power millions of data pipelines for modern analytics, data science, smart applications, and hybrid integration. **Average Rating:** 4.0/5.0 **Total Reviews:** 115 **How Do G2 Users Rate IBM StreamSets?** - **Has the product been a good partner in doing business?:** 8.2/10 (Category avg: 8.9/10) - **Quality of Support:** 8.0/10 (Category avg: 8.9/10) - **Ease of Use:** 8.4/10 (Category avg: 8.9/10) - **Ease of Admin:** 7.8/10 (Category avg: 8.5/10) **Who Is the Company Behind IBM StreamSets?** - **Seller:** [IBM](https://www.g2.com/sellers/ibm) - **Year Founded:** 1911 - **HQ Location:** Armonk, NY - **Twitter:** @IBM (709,223 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/1009/ (324,553 employees on LinkedIn®) - **Ownership:** SWX:IBM **Who Uses This Product?** - **Who Uses This:** Data Engineer, Software Engineer - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 42% Enterprise, 33% Mid-Market #### What Are IBM StreamSets's Pros and Cons? **Pros:** - Ease of Use (30 reviews) - User Interface (16 reviews) - Data Management (15 reviews) - Data Pipelining (15 reviews) - Integrations (14 reviews) **Cons:** - Learning Curve (13 reviews) - Expensive (10 reviews) - Learning Difficulty (8 reviews) - Slow Performance (8 reviews) - Steep Learning Curve (8 reviews) ### 14. [Adriel](https://www.g2.com/products/adriel/reviews) Adriel is a comprehensive AdOps platform designed to assist marketers in managing their advertising operations through no-code reporting and creative intelligence solutions. This platform caters to the needs of brands and agencies seeking to enhance their advertising strategies by providing tools that facilitate real-time data visualization and customizable dashboards. By integrating various data sources, Adriel enables users to optimize their campaigns, maximize their budgets, and ultimately drive growth. Targeted primarily at marketing professionals and agencies, Adriel serves as a vital resource for those looking to streamline their advertising efforts. The platform is particularly beneficial for teams that require a user-friendly interface to generate insights without needing extensive technical expertise. With its no-code approach, users can easily create reports and dashboards tailored to their specific needs, making it an ideal solution for both small businesses and large enterprises. One of the standout features of Adriel is its AI-driven insights, which provide users with actionable data to inform their decision-making processes. This capability allows marketers to identify trends and opportunities within their campaigns, ensuring that they can respond swiftly to changing market conditions. Additionally, the platform offers customizable widgets that enable users to visualize their data in ways that are most relevant to their objectives, enhancing the overall analytical experience. Adriel also excels in its ability to seamlessly map and blend data from various sources, allowing for a comprehensive view of campaign performance. This feature is crucial for marketers who need to consolidate information from different platforms and channels to gain a holistic understanding of their advertising efforts. Furthermore, the proactive alerts system keeps users informed of significant changes or anomalies in their data, enabling them to take immediate action when necessary. In essence, Adriel stands out in the business intelligence and reporting landscape by offering a powerful yet accessible solution for marketers. With its focus on automation, scalability, and hands-on support, it provides a robust framework for businesses looking to enhance their reporting capabilities and drive successful advertising campaigns. By leveraging Adriel's advanced features, brands can ensure they remain competitive in an ever-evolving digital marketplace. **Average Rating:** 4.5/5.0 **Total Reviews:** 41 **How Do G2 Users Rate Adriel?** - **Has the product been a good partner in doing business?:** 9.5/10 (Category avg: 8.9/10) - **Quality of Support:** 9.8/10 (Category avg: 8.9/10) - **Ease of Use:** 8.7/10 (Category avg: 8.9/10) - **Ease of Admin:** 9.2/10 (Category avg: 8.5/10) **Who Is the Company Behind Adriel?** - **Seller:** [Adriel](https://www.g2.com/sellers/adriel) - **Company Website:** https://www.adriel.com/en - **Year Founded:** 2017 - **HQ Location:** Austin, Texas - **Twitter:** @AdrielMarketing (349 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/13746025 (59 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Marketing and Advertising - **Company Size:** 73% Small-Business, 10% Mid-Market #### What Are Adriel's Pros and Cons? **Pros:** - Ease of Use (18 reviews) - Reporting (13 reviews) - Customer Support (10 reviews) - Analytics (9 reviews) - Insights (9 reviews) **Cons:** - Missing Features (4 reviews) - Complex Setup (3 reviews) - Data Management (3 reviews) - Difficult Setup (3 reviews) - Learning Curve (3 reviews) ### 15. [AWS Glue](https://www.g2.com/products/aws-glue/reviews) AWS Glue is a serverless data integration service that makes it easier for analytics users to discover, prepare, move, and integrate data from multiple sources for analytics, machine learning, and application develop-ment. You can discover and connect to 70+ diverse data sources, manage your data in a centralized data catalog, and visually create, run, and monitor ETL pipelines to load data into your data lakes. You can im-mediately search and query catalogued data using Amazon Athena, Amazon EMR, and Amazon Redshift Spectrum. **Average Rating:** 4.3/5.0 **Total Reviews:** 191 **How Do G2 Users Rate AWS Glue?** - **Has the product been a good partner in doing business?:** 8.8/10 (Category avg: 8.9/10) - **Quality of Support:** 8.3/10 (Category avg: 8.9/10) - **Ease of Use:** 8.4/10 (Category avg: 8.9/10) - **Ease of Admin:** 8.3/10 (Category avg: 8.5/10) **Who Is the Company Behind AWS Glue?** - **Seller:** [Amazon Web Services (AWS)](https://www.g2.com/sellers/amazon-web-services-aws-3e93cc28-2e9b-4961-b258-c6ce0feec7dd) - **Year Founded:** 2006 - **HQ Location:** Seattle, WA - **Twitter:** @awscloud (2,227,557 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/amazon-web-services/ (156,424 employees on LinkedIn®) - **Ownership:** NASDAQ: AMZN **Who Uses This Product?** - **Who Uses This:** Data Engineer, Software Engineer - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 48% Enterprise, 29% Mid-Market #### What Are AWS Glue's Pros and Cons? **Pros:** - Ease of Use (6 reviews) - Data Integration (3 reviews) - ETL Solutions (3 reviews) - Features (3 reviews) - Simple (3 reviews) **Cons:** - Slow Performance (3 reviews) - Debugging Difficulty (2 reviews) - Difficult Debugging (2 reviews) - Performance Issues (2 reviews) - Time-Consuming (2 reviews) ### 16. [Astro by Astronomer](https://www.g2.com/products/astro-by-astronomer/reviews) For data teams looking to increase the availability of trusted data, Astronomer provides Astro, the modern data orchestration platform, powered by Airflow. Astro enables data engineers, data scientists, and data analysts to build, run, and observe pipelines-as-code. Astronomer is the driving force behind Apache Airflow™, the de facto standard for expressing data flows as code. Airflow is downloaded more than 31 million times each month and is used by hundreds of thousands of teams around the world. **Average Rating:** 4.5/5.0 **Total Reviews:** 135 **How Do G2 Users Rate Astro by Astronomer?** - **Has the product been a good partner in doing business?:** 9.0/10 (Category avg: 8.9/10) - **Quality of Support:** 8.9/10 (Category avg: 8.9/10) - **Ease of Use:** 9.0/10 (Category avg: 8.9/10) - **Ease of Admin:** 8.8/10 (Category avg: 8.5/10) **Who Is the Company Behind Astro by Astronomer?** - **Seller:** [Astronomer](https://www.g2.com/sellers/astronomer) - **Company Website:** https://www.astronomer.io/ - **Year Founded:** 2018 - **HQ Location:** New York, US - **Twitter:** @astronomerio (19,756 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/10019299 (4,609 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Data Engineer, Senior Data Engineer - **Top Industries:** Information Technology and Services, Financial Services - **Company Size:** 47% Mid-Market, 38% Enterprise #### What Are Astro by Astronomer's Pros and Cons? **Pros:** - Ease of Use (25 reviews) - Efficiency Improvement (14 reviews) - User Interface (13 reviews) - Automation (11 reviews) - Deployment Ease (10 reviews) **Cons:** - Expensive (8 reviews) - Learning Difficulty (8 reviews) - Learning Curve (6 reviews) - Difficult Learning (5 reviews) - Feature Limitations (5 reviews) ### 17. [Adverity](https://www.g2.com/products/adverity/reviews) Centralized Data Management for the Modern Marketer Adverity is the marketing intelligence platform that empowers agencies and enterprises to transform complex data into confident, AI-powered decisions. Through automated connectivity to 600+ data sources and destinations, unrivalled data transformation capabilities, powerful data governance, and built-in agentic and conversational AI for streamlined data access and insight activation, Adverity enables smarter, faster decision-making. Adverity is used by leading brands and agencies including Unilever, Bosch, IKEA, Barilla, Forbes, GroupM, Publicis, Dentsu, and more. **Average Rating:** 4.4/5.0 **Total Reviews:** 256 **How Do G2 Users Rate Adverity?** - **Has the product been a good partner in doing business?:** 8.9/10 (Category avg: 8.9/10) - **Quality of Support:** 8.9/10 (Category avg: 8.9/10) - **Ease of Use:** 7.9/10 (Category avg: 8.9/10) - **Ease of Admin:** 8.0/10 (Category avg: 8.5/10) **Who Is the Company Behind Adverity?** - **Seller:** [Adverity GmbH](https://www.g2.com/sellers/adverity-gmbh) - **Company Website:** https://www.adverity.com - **Year Founded:** 2015 - **HQ Location:** Vienna, Austria - **Twitter:** @myadverity (1,761 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/5340622/ (292 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Data Analyst, Data Engineer - **Top Industries:** Marketing and Advertising, Information Technology and Services - **Company Size:** 42% Small-Business, 42% Mid-Market #### What Are Adverity's Pros and Cons? **Pros:** - Ease of Use (19 reviews) - Data Management (14 reviews) - Integrations (13 reviews) - Easy Integrations (12 reviews) - Customer Support (11 reviews) **Cons:** - Time-Consuming (8 reviews) - Data Management (6 reviews) - Lack of Information (6 reviews) - Time Delays (6 reviews) - Difficult Learning (5 reviews) ### 18. [AWS Lake Formation](https://www.g2.com/products/aws-lake-formation/reviews) AWS Lake Formation is a fully managed service to build, manage, secure, and share data in data lakes in days. You can centralize security and governance, and enable data sharing across the organization. **Average Rating:** 4.4/5.0 **Total Reviews:** 31 **How Do G2 Users Rate AWS Lake Formation?** - **Has the product been a good partner in doing business?:** 9.0/10 (Category avg: 8.9/10) - **Quality of Support:** 8.3/10 (Category avg: 8.9/10) - **Ease of Use:** 8.7/10 (Category avg: 8.9/10) - **Ease of Admin:** 8.0/10 (Category avg: 8.5/10) **Who Is the Company Behind AWS Lake Formation?** - **Seller:** [Amazon Web Services (AWS)](https://www.g2.com/sellers/amazon-web-services-aws-3e93cc28-2e9b-4961-b258-c6ce0feec7dd) - **Year Founded:** 2006 - **HQ Location:** Seattle, WA - **Twitter:** @awscloud (2,227,557 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/amazon-web-services/ (156,424 employees on LinkedIn®) - **Ownership:** NASDAQ: AMZN **Who Uses This Product?** - **Top Industries:** Information Technology and Services - **Company Size:** 50% Small-Business, 33% Enterprise ### 19. [SnapLogic Intelligent Integration Platform (IIP)](https://www.g2.com/products/snaplogic-intelligent-integration-platform-iip/reviews) SnapLogic is the leader in generative integration. As a pioneer in AI-led integration, the SnapLogic Platform accelerates digital transformation across the enterprise and empowers everyone to integrate faster and easier. Whether you are automating business processes, democratizing data, or delivering digital products and services, SnapLogic enables you to simplify your technology stack and take your enterprise further. Thousands of enterprises around the globe rely on SnapLogic to integrate, automate and orchestrate the flow of data across their business. Join the generative integration movement at snaplogic.com. **Average Rating:** 4.4/5.0 **Total Reviews:** 370 **How Do G2 Users Rate SnapLogic Intelligent Integration Platform (IIP)?** - **Has the product been a good partner in doing business?:** 8.8/10 (Category avg: 8.9/10) - **Quality of Support:** 8.3/10 (Category avg: 8.9/10) - **Ease of Use:** 8.8/10 (Category avg: 8.9/10) - **Ease of Admin:** 8.6/10 (Category avg: 8.5/10) **Who Is the Company Behind SnapLogic Intelligent Integration Platform (IIP)?** - **Seller:** [SnapLogic](https://www.g2.com/sellers/snaplogic) - **Company Website:** https://www.snaplogic.com - **Year Founded:** 2006 - **HQ Location:** San Mateo, CA - **Twitter:** @SnapLogic (7,354 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/210766/ (321 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Data Engineer, Consultant - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 46% Enterprise, 37% Mid-Market #### What Are SnapLogic Intelligent Integration Platform (IIP)'s Pros and Cons? **Pros:** - Ease of Use (85 reviews) - Easy Integrations (70 reviews) - Integrations (54 reviews) - User Interface (50 reviews) - Automation (43 reviews) **Cons:** - Performance Issues (31 reviews) - Poor Performance (25 reviews) - Technical Difficulties (25 reviews) - Complexity (22 reviews) - Error Reporting (22 reviews) ### 20. [Dataddo](https://www.g2.com/products/dataddo/reviews) Dataddo is the enterprise data integration platform built to eliminate the operational ownership risk of data movement. Acting as the connective backbone of your organization, we provide a fully managed connective layer that moves data from any SaaS, database, or file source to any destination - including AI agents. Our platform automatically handles API changes, schema drift, and sensitive data protection, providing full, granular visibility into every data flow across complex environments, including on-premise, hybrid, and cloud infrastructures. By treating data movement as mission-critical infrastructure rather than a project, Dataddo enables your engineering teams to deploy with total reliability, allowing them to focus on high-value AI outcomes instead of ongoing pipeline maintenance. **Average Rating:** 4.7/5.0 **Total Reviews:** 182 **How Do G2 Users Rate Dataddo?** - **Has the product been a good partner in doing business?:** 9.0/10 (Category avg: 8.9/10) - **Quality of Support:** 9.2/10 (Category avg: 8.9/10) - **Ease of Use:** 8.9/10 (Category avg: 8.9/10) - **Ease of Admin:** 8.8/10 (Category avg: 8.5/10) **Who Is the Company Behind Dataddo?** - **Seller:** [Dataddo](https://www.g2.com/sellers/dataddo) - **Year Founded:** 2015 - **HQ Location:** Praha 7, CZ - **Twitter:** @dataddo (230 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/dataddo/ (27 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Marketing and Advertising, Computer Software - **Company Size:** 52% Small-Business, 40% Mid-Market #### What Are Dataddo's Pros and Cons? **Pros:** - Connectivity (2 reviews) - Customer Support (2 reviews) - Customization (2 reviews) - Data Management (2 reviews) - Ease of Use (2 reviews) **Cons:** - Complexity (1 reviews) - Complex Setup (1 reviews) - Learning Curve (1 reviews) - Learning Difficulty (1 reviews) - Limitations (1 reviews) ### 21. [Integrate.io](https://www.g2.com/products/integrate-io/reviews) Integrate.io is a low-code data pipeline platform specializing in Operational ETL so companies can automate business processes and manual data preparation. Its four core use cases focus on: 1) File data preparation and B2B data sharing 2) Preparing and loading data to CRMs and ERPs such as Salesforce, NetSuite, and HubSpot 3) Powering data products with real-time database replication 4) Transforming and centralizing data to data warehouse for analytics **Average Rating:** 4.3/5.0 **Total Reviews:** 210 **How Do G2 Users Rate Integrate.io?** - **Has the product been a good partner in doing business?:** 9.2/10 (Category avg: 8.9/10) - **Quality of Support:** 9.3/10 (Category avg: 8.9/10) - **Ease of Use:** 8.4/10 (Category avg: 8.9/10) - **Ease of Admin:** 8.7/10 (Category avg: 8.5/10) **Who Is the Company Behind Integrate.io?** - **Seller:** [Integrate.io](https://www.g2.com/sellers/integrate-io) - **Year Founded:** 2012 - **HQ Location:** San Francisco, CA - **Twitter:** @Integrateio (4,290 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/2709076/ (25 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Data Engineer, Data Analyst - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 50% Mid-Market, 32% Small-Business #### What Are Integrate.io's Pros and Cons? **Pros:** - Ease of Use (11 reviews) - Customer Support (8 reviews) - Easy Integrations (7 reviews) - Features (7 reviews) - Automation (6 reviews) **Cons:** - Learning Difficulty (4 reviews) - Poor Documentation (4 reviews) - Limited Integrations (3 reviews) - API Issues (2 reviews) - API Limitations (2 reviews) ### 22. [Nexla](https://www.g2.com/products/nexla/reviews) Nexla is an enterprise-grade, AI-powered data integration platform designed to help organizations unlock data from any source and transform it into production-ready data products for AI and agents. With support for 550+ pre-built connectors and multiple integration styles, including ELT, ETL, streaming, APIs, and agentic RAG, the platform enables teams to build and manage data flows without writing code. Trusted by leading enterprises, Nexla processes over one trillion records per month across industries, ​​showcasing its ability to handle large volumes of data while maintaining performance and reliability. Innovators like Autodesk, DoorDash, Instacart, Johnson & Johnson, LinkedIn, and LiveRamp rely on Nexla to keep mission-critical data flowing seamlessly across their enterprises. Key features of Nexla include flexible deployment across cloud, hybrid, and on-premises environments, ensuring compliance with enterprise-grade security standards such as SOC 2 Type II, GDPR, CCPA, and HIPAA. Nexla delivers 10x faster implementation than traditional alternatives, turning data challenges and variety into competitive advantages. Try our AI Data Engineer at https://express.dev Increase the impact of your data engineering team with next-gen data integration: ✅ Eliminate costly replications & reduce storage bills ✅ Increase engineering productivity & capacity for innovation ✅ Empower users with Pro/Low/No-code collaboration ✅ Cut out maintenance with data validation, quality monitoring, & alerts ✅ Build production-ready custom GenAI applications Go beyond one traditional integration pattern, and invest in data architecture that supports: ✅ Any integration pattern (ELT, ETL, API / API proxy, & RAG - Retrieval Augmented Generation) ✅ Bi-directional connectors out of the box & on demand ✅ Any processing speed (streaming, real-time, batch) ✅ Unstructured, structured, or semi-structured data ✅ Complete data lineage search & tagging for governance ✅ Metadata-driven architecture for agility & scale Nexla is a Gartner Cool Vendor and pairs perfectly with the technologies you rely on: ✅ Compute: AWS, Azure, Google Cloud, On-Premise ✅ Storage: S3, Redshift, BigQuery, Snowflake, Oracle, Databricks, Kafka, Redis, MongoDB, Postgres, MySQL ✅ Applications: SAP, Salesforce, Marketo, Hubspot, Amazon Seller Central, Google Ads, API, Salesforce ✅ Catalogs: Alation, Collibra, data.world ✅ Webhooks, emails, FTP & APIs ✅ Vector database & LLM: Pinecone, GPT, Falcon, LLaMDa And many more Differentiators & Awards 🏆 2025 Highest Rating Gartner Peer Insights™ Voice of the Customer for Data Integration Tools 🏆 2024 Highest Rating Gartner Peer Insights™ Voice of the Customer for Data Integration Tools 🏆 2023 Highest Rating Gartner Peer Insights™ Voice of the Customer for Data Integration Tools 🏆 2022 Highest Rating Gartner Peer Insights™ Voice of the Customer for Data Integration Tools **Average Rating:** 4.6/5.0 **Total Reviews:** 62 **How Do G2 Users Rate Nexla?** - **Has the product been a good partner in doing business?:** 9.1/10 (Category avg: 8.9/10) - **Quality of Support:** 8.9/10 (Category avg: 8.9/10) - **Ease of Use:** 8.7/10 (Category avg: 8.9/10) - **Ease of Admin:** 8.8/10 (Category avg: 8.5/10) **Who Is the Company Behind Nexla?** - **Seller:** [Nexla](https://www.g2.com/sellers/nexla) - **Company Website:** https://www.nexla.com/ - **Year Founded:** 2016 - **HQ Location:** San Mateo, California - **Twitter:** @NexlaInc (946 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/nexla/ (76 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Computer Software, Insurance - **Company Size:** 41% Mid-Market, 32% Small-Business #### What Are Nexla's Pros and Cons? **Pros:** - Ease of Use (21 reviews) - Automation (14 reviews) - Data Management (14 reviews) - Integrations (13 reviews) - Data Integration (10 reviews) **Cons:** - Learning Difficulty (7 reviews) - Slow Performance (7 reviews) - Difficult Learning (6 reviews) - Learning Curve (6 reviews) - Poor Documentation (6 reviews) ### 23. [Syncari](https://www.g2.com/products/syncari/reviews) Syncari is an AI-ready, Agentic MDM platform that unifies, governs, and activates trusted data across all your systems, domains, and cloud infrastructure. Built for enterprises navigating the complexity of multi-agent environments and AI-driven operations, Syncari automates core data management workflows—from data modeling and lineage to validation and remediation—without needing heavy IT resources. At the heart of Syncari is its patented multi-directional sync, delivering real-time, bi-directional data consistency across CRMs, ERPs, cloud platforms, and data warehouses—without custom code or middleware. Syncari ensures continuously clean, synchronized, and governed data flows throughout your enterprise and is always ready for analytics, AI models, and operational use. Whether you're powering AI copilots, managing complex entity relationships, or standardizing data pipelines, Syncari helps you move beyond just managing data—to activating it. Why Syncari? -Syncari Agentic MDM™: Designed for orchestrating trusted data across AI agents and teams -Patented Multi-Directional Sync: Real-time updates across all connected platforms -Agentic Ops: Schema sync, field mapping, DQ enforcement, and remediation -Entity Resolution: Consolidate and deduplicate records across domains -Composable + Cloud-First: Built to plug into your existing SaaS and data stack -Low-Code / No-Code: Accessible to IT, data teams, RevOps, and business users alike Core Capabilities Unify, Sync, Automate, Activate, Model, Catalog, Lineage, Transform, Standardize, Verify, Remediate, Observe, Report, Consume Top Use Cases - Customer Master: Build a unified customer profile across GTM systems - Product Master: Align and enrich product data across eCommerce and ERP - Hierarchy Master: Govern legal entities, accounts, and territories - Analytics MDM: Push AI-ready data into BI tools and ML workflows - Data Products: Operationalize governed datasets for internal and external use - Data Quality: Automatically identify, validate, standardize, and remediate data issues across systems - MDM for Snowflake: Sync and manage master data directly inside Snowflake - MDM for GCP: Connect, unify, and activate trusted data in BigQuery and GCP tools - MDM for Your Data Warehouse: Maintain clean, governed, query-ready data across your cloud warehouse infrastructure -MCP Server for your unified data **Average Rating:** 4.8/5.0 **Total Reviews:** 41 **How Do G2 Users Rate Syncari?** - **Has the product been a good partner in doing business?:** 10.0/10 (Category avg: 8.9/10) - **Quality of Support:** 9.9/10 (Category avg: 8.9/10) - **Ease of Use:** 7.9/10 (Category avg: 8.9/10) - **Ease of Admin:** 8.4/10 (Category avg: 8.5/10) **Who Is the Company Behind Syncari?** - **Seller:** [Syncari](https://www.g2.com/sellers/syncari) - **Year Founded:** 2019 - **HQ Location:** Newark, California - **Twitter:** @syncari (234 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/syncari/ (49 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Computer Software, Information Technology and Services - **Company Size:** 51% Mid-Market, 44% Small-Business ### 24. [ClicData](https://www.g2.com/products/clicdata/reviews) ClicData is a cloud-based modern data platform that combines features across several categories, including Business Intelligence (BI), Data Analytics, ETL (Extract, Transform, Load), Data Warehousing, Embedded Analytics, and Data Management. It is designed to support organizations in building and maintaining complete data workflows in a single environment. The platform offers tools that enable customers to work across the entire data lifecycle, from data ingestion to transformation and visualization. It can be used by technical teams, such as data engineers and analysts, as well as by operational and business users who need reliable access to structured, consistent, and timely data. ClicData supports a range of use cases by allowing users to: • Connect to a wide range of data sources including databases, cloud applications, and flat files • Store data using an integrated data warehouse and data lake structure • Cleanse and transform data with built-in ETL tools using either no-code interfaces or SQL • Visualize data through dashboards and reports that can be shared internally or externally • Automate data updates, alerts, and report delivery through scheduling and workflow tools • Embed dashboards into third-party platforms or client-facing applications • Extend analysis with support for Python scripts for statistical or machine learning use cases ClicData is used by organizations in various industries including retail, healthcare, media, manufacturing, and public services. Its flexibility makes it applicable to both centralized data teams and smaller operational groups managing their own analytics needs. By bringing together multiple data capabilities into one platform, ClicData allows teams to reduce reliance on multiple disconnected tools and streamline how they manage and use data across their organization. **Average Rating:** 4.4/5.0 **Total Reviews:** 35 **How Do G2 Users Rate ClicData?** - **Has the product been a good partner in doing business?:** 8.8/10 (Category avg: 8.9/10) - **Quality of Support:** 8.9/10 (Category avg: 8.9/10) - **Ease of Use:** 8.2/10 (Category avg: 8.9/10) - **Ease of Admin:** 8.8/10 (Category avg: 8.5/10) **Who Is the Company Behind ClicData?** - **Seller:** [ClicData](https://www.g2.com/sellers/clicdata) - **Year Founded:** 2008 - **HQ Location:** Nord, France - **Twitter:** @ClicData (809 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/278851/ (46 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 50% Small-Business, 33% Mid-Market ### 25. [Airbyte](https://www.g2.com/products/airbyte/reviews) Airbyte is an open-core data integration platform designed to facilitate the seamless movement of both structured and unstructured data across a wide array of sources and destinations. This platform empowers users to create custom data pipelines that cater to their specific needs, allowing teams to manage and control their data workflows effectively. With Airbyte, organizations can streamline their data integration processes, making it easier to harness the power of their data for analysis and decision-making. Targeted primarily at data engineers, analysts, and organizations that require robust data management solutions, Airbyte serves a diverse range of industries. Its user-friendly interface and extensive library of connectors enable teams to integrate data from various platforms, including databases, APIs, and cloud services. This versatility makes Airbyte particularly valuable for businesses looking to consolidate their data sources into a single, coherent framework, enhancing their analytical capabilities and operational efficiency. One of the key features of Airbyte is its open-source nature, which allows users to customize and extend the platform according to their unique requirements. This flexibility is complemented by a growing community of contributors who continuously develop new connectors and enhancements. Additionally, Airbyte supports batch data synchronization, ensuring that users can access the most up-to-date information regardless of their operational needs. This capability is crucial for organizations that rely on timely data for critical decision-making processes. Airbyte also stands out with its user-friendly interface that simplifies the process of setting up and managing data pipelines. Users can easily configure connections, monitor data flows, and troubleshoot issues without extensive technical expertise. This accessibility reduces the barrier to entry for teams that may not have dedicated data engineering resources, enabling a broader range of users to leverage data integration effectively. In summary, Airbyte is a powerful data integration platform that offers flexibility, customization, and ease of use for organizations seeking to optimize their data workflows. By providing a platform that supports a wide variety of data sources and destinations, Airbyte empowers teams to take control of their data integration processes, ultimately driving better insights and informed decision-making across the enterprise. **Average Rating:** 4.4/5.0 **Total Reviews:** 76 **How Do G2 Users Rate Airbyte?** - **Has the product been a good partner in doing business?:** 8.5/10 (Category avg: 8.9/10) - **Quality of Support:** 8.0/10 (Category avg: 8.9/10) - **Ease of Use:** 9.0/10 (Category avg: 8.9/10) - **Ease of Admin:** 8.4/10 (Category avg: 8.5/10) **Who Is the Company Behind Airbyte?** - **Seller:** [Airbyte](https://www.g2.com/sellers/airbyte) - **Company Website:** https://airbyte.com/ - **Year Founded:** 2020 - **HQ Location:** San Francisco, US - **Twitter:** @airbytehq (14,189 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/64265083 (126 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Computer Software, Financial Services - **Company Size:** 57% Small-Business, 36% Mid-Market #### What Are Airbyte's Pros and Cons? **Pros:** - Ease of Use (43 reviews) - Connectors Quantity (26 reviews) - Simple (15 reviews) - Setup Ease (12 reviews) - Quick Setup (11 reviews) **Cons:** - Poor Documentation (8 reviews) - Difficult Setup (7 reviews) - Error Reporting (6 reviews) - Expensive (5 reviews) - Limited Connectors (5 reviews) ## 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? - [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) --- ## 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.