# Best Big Data Integration Platforms - Page 5 *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 (846 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 (707 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 (748 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 | [Amazon Redshift](https://www.g2.com/products/amazon-redshift/reviews) | 4.3/5.0 (370 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)" | | 6 | [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)" | | 7 | [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 | "[SnapLogic Snaps Make No-Code Data Integration Simple and Powerful](https://www.g2.com/survey_responses/snaplogic-intelligent-integration-platform-iip-review-13058311)" | | 8 | [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)" | | 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=10898&focus%5B%5D=52204&focus%5B%5D=2975&focus%5B%5D=41374) Highlighted products: Google Cloud BigQuery, Alteryx, Snowflake, Workato, Amazon Redshift, Azure Data Factory, SnapLogic Intelligent Integration Platform (IIP), and Maia. 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=amazon-redshift&focus%5B%5D=azure-data-factory&focus%5B%5D=snaplogic-intelligent-integration-platform-iip&focus%5B%5D=matillion-maia) ## 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 (+0.37%) - Among all products in this category, Control-M recorded the largest rating increase compared to last month *Last updated: July 14, 2026* ## How Does G2 Rank Big Data Integration Platforms Products? **Why You Can Trust G2's Software Rankings:** - 30 Analysts and Data Experts - 9,400+ 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. ## Which Big Data Integration Platforms Is Best for Your Use Case? - **Leader:** [Google Cloud BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews) - **Highest Performer:** [5X](https://www.g2.com/products/5x/reviews) - **Easiest to Use:** [5X](https://www.g2.com/products/5x/reviews) - **Top Trending:** [Astro by Astronomer](https://www.g2.com/products/astro-by-astronomer/reviews) - **Best Free Software:** [Alteryx](https://www.g2.com/products/alteryx/reviews) --- **Sponsored** ### Cloudera Cloudera is the only hybrid data and AI platform company that large organizations trust to bring AI to their data anywhere it lives. Unlike other providers, Cloudera delivers a consistent cloud experience that converges public clouds, on-prem data centers, and the edge, leveraging a proven open-source foundation. As the pioneer in big data, Cloudera empowers businesses to apply AI and assert control over 100% of their data, in all forms, improving security, governance, and real-time and predictive insights. The world’s largest brands across all industries rely on Cloudera to transform decision-making and ultimately boost bottom lines, safeguard against threats, and save lives. The Cloudera data and AI platform includes: Cloudera AI: Deploy and scale any AI model, anywhere. Cloudera brings compute to governed data where it lives for Private AI anywhere by design. Complete control, security, and governance of mission-critical data, models, agents, and inference ensure faster sovereign AI deployments. Cloudera Data-in-Motion: Make fast decisions from real-time data anywhere. Move data with any structure from any source to any destination seamlessly across hybrid environments, enabling in-the-moment business-critical decisions by processing and analyzing real-time data anywhere, from the edge to AI, as business happens. Cloudera Open Data Lakehouse: Process any data, anywhere, for actionable insights. Make smart decisions with an open data lakehouse powered by Apache Iceberg that delivers trusted, reliable, and unified data to fuel agents, AI applications, and analytics, improving collaboration, breaking silos, and simplifying sharing. Cloudera Unified Data Fabric: Unify security and governance across the entire data estate. Move beyond fragmented data management: Break down silos and connect disparate data sources intelligently and securely to provide a unified view of all organizational data and centralized end-to-end control across complex hybrid data environments. [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=2026-07-15T07%3A47%3A15Z&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=1886&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=f73aabe72f2ad44bc9745e28e53628c7b8b07c3aa7ad793061143b179bffcd18&secure%5Burl%5D=https%3A%2F%2Fwww.cloudera.com%2Fproducts%2Fcloudera-data-platform%2Fcdp-demos.html%3Finternal_link%3Dp18%23get-started&secure%5Burl_type%5D=custom_url) --- ## What Are the Top-Rated Big Data Integration Platforms Products in 2026? ### 1. [Zengines](https://www.g2.com/products/zengines/reviews) Zengines is a technology company that transforms how organizations handle data migrations and mainframe modernization by empowering business users and technical specialists alike with modern AI-powered tools. Our platform includes end-to-end Data Migration tools and Mainframe Data Lineage solutions that illuminate and decode "black box" legacy systems, accelerating projects by 80% while significantly reducing risk and cost. We primarily serve financial services firms and their technology partners who struggle with unpredictable data and legacy systems during critical transformation initiatives. Global organizations use Zengines across their enterprise for the constant stream of initiatives that involve systems change - core conversions, systems implementations, new customer onboarding, audit, and compliance reporting. **Average Rating:** 5.0/5.0 **Total Reviews:** 3 **How Do G2 Users Rate Zengines?** - **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:** 8.3/10 (Category avg: 8.5/10) **Who Is the Company Behind Zengines?** - **Seller:** [Zengines](https://www.g2.com/sellers/zengines) - **Year Founded:** 2020 - **HQ Location:** Bedford, US - **LinkedIn® Page:** https://www.linkedin.com/company/zengines/ (17 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 67% Enterprise, 33% Mid-Market #### What Are Zengines's Pros and Cons? **Pros:** - Ease of Use (2 reviews) - Innovation (2 reviews) - AI Integration (1 reviews) - Communication (1 reviews) - Customer Support (1 reviews) **Cons:** - Mapping Issues (1 reviews) ### What Do G2 Reviewers Say About Zengines? *AI-generated summary from verified user reviews* **Pros:** - Users commend Zengines for its **frictionless user experience** and ease of implementation with legacy applications. - Users appreciate the **innovative approach** of Zengines, noting significant improvements in data handling and user experience. - Users praise the **seamless AI integration** of Zengines, enhancing the analysis of complex legacy applications effortlessly. - Users commend the **excellent communication** of the Zengines team, highlighting their collaborative vision and problem-solving focus. - Users commend the **amazing customer support** team for their vision and problem-solving focus. **Cons:** - Users desire more clarity on **mapping issues** , particularly regarding compliance and new domain integrations. #### What Are Recent G2 Reviews of Zengines? **"[Innovative - Frictionless Data Migration](https://www.g2.com/survey_responses/zengines-review-11246885)"** **Rating:** 5.0/5.0 stars *— Anil B.* [Read full review](https://www.g2.com/survey_responses/zengines-review-11246885) --- **"[Zengines - Excellent AI tool to analyze Legacy Applications](https://www.g2.com/survey_responses/zengines-review-11922562)"** **Rating:** 5.0/5.0 stars *— Verified User in Investment Banking* [Read full review](https://www.g2.com/survey_responses/zengines-review-11922562) --- ### 2. [1Platform](https://www.g2.com/products/1platform/reviews) 1Platform by Polestar Analytics is a unified, low-code data intelligence ecosystem that transforms enterprise data management through its powerful orchestration engine, AI capabilities, and comprehensive analytics portal. Built with a no-code platform for data engineering, it seamlessly integrates 100+ data sources while providing automated data lake acceleration, historical data migration, and comprehensive data quality scorecards with execution logs for complete governance. What sets 1Platform apart is its ability to deliver actionable intelligence at scale through unified insights access, agentic and generative AI capabilities that go beyond data summarization to extract additional insights and advanced preloaded, scalable and customisable LLM and reasoning models reducing time and talent requirement. The platform operates through a single, intuitive interface across any cloud environment with modular, plug-and-play architecture, featuring access-based configuration for analytics, dashboard management, and a comprehensive notifications hub for tracking key activities. Backed by 350+ successful clients, 1,000+ implementations, and an exceptional 87% repeat business rate across 20+ global markets, Polestar Analytics delivers the agility, speed, and intelligence that modern enterprises demand to maintain their competitive edge. **Who Is the Company Behind 1Platform?** - **Seller:** [Polestar Analytics](https://www.g2.com/sellers/polestar-analytics) - **Year Founded:** 2012 - **HQ Location:** Plano, US - **Twitter:** @PolestarLLP (508 Twitter followers) - **LinkedIn® Page:** http://www.linkedin.com/company/polestarsolutions%26services (634 employees on LinkedIn®) ### 3. [Apache Hop](https://www.g2.com/products/apache-hop/reviews) A workflow processing engine for data transformation pipelines, written in Java. With desktop and web GUIs for pipeline construction & operation, and workflow management. No code pipeline configuration. Extensive connections & transform ability. **Who Is the Company Behind Apache Hop?** - **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®) ### 4. [Athenian.io](https://www.g2.com/products/athenian-io/reviews) AI-Powered Data Automation for SAP & Enterprise Systems. Athenian.io is a next-generation enterprise data platform that automates the entire data lifecycle—from data modeling to API creation, infrastructure deployment, and real-time analytics. Unlike traditional platforms that require manual ETL, complex pipelines, and expensive engineering, Athenian.io uses AI to generate fully functional SAP-ready applications in seconds—without writing a single line of code. Key Features & Capabilities AI-Powered Data Modeling – Convert natural language into fully structured data models. ✅ End-to-End Automation – Instantly generate data models, APIs, infrastructure, and analytics dashboards. ✅ SAP & ERP Integration – Ready for SAP S/4HANA, SAP BW, and other enterprise ERP systems. ✅ No-Code & Low-Code – Business users can build applications without IT bottlenecks. ✅ Metadata-Driven Architecture – Athenian’s metadata engine intelligently structures relationships, tables, and analytics. ✅ Cost Savings & Efficiency – Reduces SAP & data integration costs by over 60% while accelerating time-to-insights. Who Uses Athenian.io? 💼 SAP Consultants & ERP Teams – Automate SAP data modeling, reporting, and analytics. 💡 CIOs, CTOs & IT Leaders – Streamline enterprise data integration & application deployment. 📊 Business Intelligence & Data Teams – Build data models, dashboards, and APIs without code. ⚙️ Enterprise Architects & Data Engineers – Automate complex data transformations & workflows. Why Athenian.io? (Competitive Edge) 🚀 No More Data Pipelines – AI Automates Everything. 💰 Cuts SAP Data Integration Costs by 60%+. ⚡ Deploys Full ERP Applications in Seconds, Not Months. 🔄 Fully AI-Driven, No-Code, & ERP-Ready. **Who Is the Company Behind Athenian.io?** - **Seller:** [Athenian.io](https://www.g2.com/sellers/athenian-io) - **Year Founded:** 2017 - **HQ Location:** Brisbane City, AU - **LinkedIn® Page:** https://www.linkedin.com/company/athenian.io-pty-ltd (2 employees on LinkedIn®) ### 5. [Attlaz](https://www.g2.com/products/attlaz/reviews) Our vision is to make connecting platforms easy to manage, accessible, transparent, stable and collaborative. Ultimately this empowers clients to take control of their data, saving money and time in the process. **Who Is the Company Behind Attlaz?** - **Seller:** [Attlaz](https://www.g2.com/sellers/attlaz) - **Year Founded:** 2017 - **HQ Location:** London, GB - **LinkedIn® Page:** https://www.linkedin.com/company/attlaz (2 employees on LinkedIn®) ### 6. [Besyncly](https://www.g2.com/products/besyncly/reviews) Besyncly is a powerful cloud integration platform that connects your critical business platforms, including accounting, ERP, CRM, ecommerce, ticketing and fundraising systems, by seamlessly transferring data between them. Designed by Eureka Solutions, it eliminates the need for manual data entry and helps organisations of all sizes improve accuracy, visibility and efficiency. With Besyncly, your systems work together as one. Whether you need to link Sage 50, Sage 200, iplicit or NetSuite with platforms such as Shopify, HubSpot, Salesforce or JustGiving, Besyncly ensures that every transaction, update and record is automatically synchronised. This creates a single, consistent view of your data across finance, operations, sales and customer teams. Every Besyncly project benefits from a fully managed implementation, handled by experienced integration specialists. We take the time to understand your systems, data flows and business processes, then configure Besyncly to deliver exactly what you need – whether that’s an out-of-the-box connector or a bespoke setup for complex integrations. Once live, you’re supported by the Eureka Solutions team; our experts continually monitor performance, resolve any issues and ensure that your data keeps moving between platforms. The Besyncly dashboard provides simple, day-to-day visibility of your integrations where you can see how many transactions have been processed, what’s scheduled and whether any have failed. It’s designed for quick daily monitoring, while the technical management and troubleshooting are fully handled by the support team behind the scenes. Built with scalability in mind, Besyncly suits organisations ranging from SMEs to enterprise-level operations. It’s already trusted by businesses, charities and organisations across retail, sport, entertainment, manufacturing and the non-profit sector. Our library of connectors continues to grow, with new integrations released regularly in response to customer demand and changes in technology. We work hard to ensure Besyncly remains a future-focused solution that can evolve alongside your organisation. Key benefits: • Fully managed setup and ongoing expert support • Connects accounting, ERP, CRM, ecommerce, ticketing and fundraising systems • Automates the import and export of key business data • Reduces manual effort and eliminates duplication • Provides real-time visibility through an easy-to-use dashboard • Wide and growing range of platform connectors • Backed by integration specialists with decades of Sage and NetSuite expertise Besyncly keeps your organisation connected, your data accurate, and your teams aligned, letting you focus on what really matters: running your business. **Who Is the Company Behind Besyncly?** - **Seller:** [Eureka Solutions](https://www.g2.com/sellers/eureka-solutions) - **HQ Location:** Glasgow, GB - **LinkedIn® Page:** https://www.linkedin.com/company/besyncly (4 employees on LinkedIn®) ### 7. [Be-XConnect](https://www.g2.com/products/be-xconnect/reviews) Be-XConnect is an on-premise software designed to combine data collection and integration capabilities in a single software. Users can collect data from devices, manufacturing machines, laboratory equipment, dispensing machines, etc. as well as from reports and data bases. Users can parse the collected data to retrieve only the values they need. Be-XConnect can also be used to integrate the collected values to other devices or platforms and to enable M2M communications. Supported protocols and formats for data collection and integration RS232 TCP-IP OPC-DA MS SQL DB Oracle DB MS Excel XML CSV Plain Text MS Azure for data integration only. Be-XConnect is simple to implement and flexible, enabling users to complete data collection and integration projects on their own. **Who Is the Company Behind Be-XConnect?** - **Seller:** [Beryllium](https://www.g2.com/sellers/beryllium) - **Year Founded:** 1998 - **HQ Location:** San Juan, US - **LinkedIn® Page:** https://www.linkedin.com/company/beryllium-corporation (12 employees on LinkedIn®) ### 8. [BigBox](https://www.g2.com/products/bigbox/reviews) BIGBOX provides End-to-End Big Data Platform to generate actionable insights according to the company's operational and business needs, on premises, in hybrid or public clouds. Our technology has seen rapid adoption from major brands and services provider in Asia Pacific, including banks, retailers, telecommunication, healthcare, energy, media, education, government and others. **Who Is the Company Behind BigBox?** - **Seller:** [BIGBOX](https://www.g2.com/sellers/bigbox) - **Year Founded:** 2017 - **HQ Location:** Bandung, ID - **LinkedIn® Page:** http://www.linkedin.com/company/bigboxcoid (29 employees on LinkedIn®) ### 9. [Blossom Sky](https://www.g2.com/products/blossom-sky/reviews) Databloom is a distributed data access and analytics company that develops "Blossom Sky", an AI-Powered Data Platform Integration as a Service. Blossom Sky enables distributed data processing across multiple data processing engines and accelerates digital transformation by eliminating complex data management processes. **Who Is the Company Behind Blossom Sky?** - **Seller:** [Databloom](https://www.g2.com/sellers/databloom) - **Year Founded:** 2023 - **HQ Location:** Miami, US - **LinkedIn® Page:** https://www.linkedin.com/company/scalytics (7 employees on LinkedIn®) ### 10. [CDAP](https://www.g2.com/products/cdap/reviews) CDAP lets developers, business analysts and data scientists focus on insights, analytics and business value instead of wrestling with infrastructure, and integration. **Who Is the Company Behind CDAP?** - **Seller:** [CDAP](https://www.g2.com/sellers/cdap) - **HQ Location:** N/A - **LinkedIn® Page:** https://www.linkedin.com/company/No-Linkedin-Presence-Added-Intentionally-By-DataOps (1 employees on LinkedIn®) ### 11. [Dassault Exalead](https://www.g2.com/products/dassault-exalead/reviews) Bridging the gap between people and today???s distributed, diverse big data In the enterprise and across the Internet, over 110 million people worldwide rely on EXALEAD CloudView?? to intuitively search, explore, and analyze information. **Who Is the Company Behind Dassault Exalead?** - **Seller:** [Dassault Systemes](https://www.g2.com/sellers/dassault-systemes) - **Year Founded:** 1981 - **HQ Location:** Velizy-Villacoublay - **Twitter:** @Dassault3DS (74,082 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/3896/ (27,414 employees on LinkedIn®) - **Ownership:** EPA: DSY.PA **Who Uses This Product?** - **Company Size:** 100% Enterprise, 100% Mid-Market #### What Are Recent G2 Reviews of Dassault Exalead? **"[Functionally very powerful](https://www.g2.com/survey_responses/dassault-exalead-review-5228975)"** **Rating:** 4.0/5.0 stars *— Verified User in Information Technology and Services* [Read full review](https://www.g2.com/survey_responses/dassault-exalead-review-5228975) --- #### What Are G2 Users Discussing About Dassault Exalead? - [What is Dassault Exalead used for?](https://www.g2.com/discussions/what-is-dassault-exalead-used-for) ### 12. [Data Collector as a Service (DaaS)](https://www.g2.com/products/data-collector-as-a-service-daas/reviews) DaaS is a Cloud-based containerized software solution that gives our customers an open, faster and more secure way to fetch data ( both Structured and Non-structured data) from varied Source systems and feed into their platform. **Who Is the Company Behind Data Collector as a Service (DaaS)?** - **Seller:** [Sacumen](https://www.g2.com/sellers/sacumen) - **Year Founded:** 2015 - **HQ Location:** Bangalore, IN - **LinkedIn® Page:** https://www.linkedin.com/company/sacumensecurity (161 employees on LinkedIn®) ### 13. [Datajoin](https://www.g2.com/products/datajoin/reviews) Datajoin is a SaaS platform designed to help B2B marketers seamlessly integrate their marketing technology stacks through proprietary 'Micro Integrations.' By connecting leading web analytics tools like Google Analytics and Adobe Analytics with CRM systems such as Salesforce, Datajoin provides a unified view of the customer journey. This integration enables marketing and sales teams to bridge data silos, leading to more informed decision-making and optimized marketing strategies. Key Features and Functionality: - Micro Integrations: Datajoin's unique, no-code integrations synchronize customer data between various marketing applications without the need for engineering resources, facilitating quick and efficient data consolidation. - Comprehensive Data Modeling: The platform expertly structures and organizes data from multiple sources, ensuring it's ready for downstream analysis and applications, thereby providing a scalable, high-quality data foundation. - Extensive Integrations: Datajoin supports integration with top web analytics and CRM platforms, including Google Analytics, Adobe Analytics, and Salesforce, enabling a cohesive marketing technology ecosystem. Primary Value and User Solutions: Datajoin addresses the common challenge of fragmented marketing technology stacks by providing seamless integrations that unify disparate data sources. This unification empowers marketing and sales teams with actionable insights, leading to improved customer targeting, enhanced campaign performance, and a more streamlined customer journey. By eliminating the need for extensive engineering resources and reducing integration timelines from months to days, Datajoin significantly enhances operational efficiency and marketing effectiveness. **Who Is the Company Behind Datajoin?** - **Seller:** [Datajoin](https://www.g2.com/sellers/datajoin) - **Year Founded:** 2017 - **HQ Location:** Salt Lake City, Utah, United States - **LinkedIn® Page:** https://www.linkedin.com/company/fullcast-com (139 employees on LinkedIn®) ### 14. [DigitalRoute](https://www.g2.com/products/digitalroute/reviews) With over 400 global clients, DigitalRoute is the leading provider of solutions that enable hybrid and usage-based pricing for as-a-service businesses across all industries, including Telecoms and the SaaS market. From our extensive usage data management platform, data mediation, usage metering and usage intelligence capabilities, our customers can integrate, collect, process, meter and distribute system-ready records for billing, other quote-to-cash systems and analytics. We align with any deployment preferences. **Who Is the Company Behind DigitalRoute?** - **Seller:** [DigitalRoute](https://www.g2.com/sellers/digitalroute) - **Year Founded:** 2000 - **HQ Location:** Härjedalens kommun, Jämtland County, Sweden - **Twitter:** @Digital_Route (514 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/digital-route/ (242 employees on LinkedIn®) ### 15. [ElixirData - Modern Big Data Integration Platform](https://www.g2.com/products/elixirdata-modern-big-data-integration-platform/reviews) XenonStack is a software company that specializes in product development and providing DevOps, big data integration, real time analytics and data science solutions. **Who Is the Company Behind ElixirData - Modern Big Data Integration Platform?** - **Seller:** [XenonStack](https://www.g2.com/sellers/xenonstack) - **Year Founded:** 2016 - **HQ Location:** Newark, US - **Twitter:** @XenonStack (956 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/xenonstack/ (79 employees on LinkedIn®) ### 16. [Equalum](https://www.g2.com/products/equalum/reviews) Equalum is a fully-managed, end-to-end data pipeline platform built for extreme performance and scalability. Equalum combines our unique data ingestion technology with the power of open source frameworks like Apache Kafka, Spark, and other widely deployed open source projects. **Who Is the Company Behind Equalum?** - **Seller:** [Equalum](https://www.g2.com/sellers/equalum) - **Year Founded:** 2015 - **HQ Location:** Boston, US - **LinkedIn® Page:** https://www.linkedin.com/company/9489281 (8 employees on LinkedIn®) ### 17. [ERI Platform](https://www.g2.com/products/eri-platform/reviews) ERI platform includes the M3T4 Studio (M3), an extensible, Eclipse based JAVA platform that leverages the power of data semantics to stitch your business’s most critical information together. **Who Is the Company Behind ERI Platform?** - **Seller:** [Metatomix](https://www.g2.com/sellers/metatomix) - **Year Founded:** 2001 - **HQ Location:** United States - **LinkedIn® Page:** http://www.linkedin.com/company/metatomix (14 employees on LinkedIn®) ### 18. [Interloop Mission Control](https://www.g2.com/products/interloop-mission-control/reviews) Interloop® empowers teams using Microsoft Fabric to build and deliver Data Analytics & Al Solutions Faster. Interloop Mission Control works seamlessly with Microsoft Fabric to: • Connect - Sync data across 500+ external sources in minutes. • Monitor - Proactively monitor and handle incidents with ease. • Explore - Enable self-service analysis for non-technical users. • Share - Share datasets &dashboards with consumers easily. Interloop reduces engineering workloads and costs, enabling teams to focus on addressing the business challenges that matter. **Who Is the Company Behind Interloop Mission Control?** - **Seller:** [Interloop](https://www.g2.com/sellers/interloop) - **Year Founded:** 2015 - **HQ Location:** Charleston, US - **LinkedIn® Page:** https://www.linkedin.com/company/interloopdata (33 employees on LinkedIn®) ### 19. [Mugen](https://www.g2.com/products/mugen/reviews) Mµgen supports the promotion of DX by companies by expanding the limits of data utilization infinitely **Who Is the Company Behind Mugen?** - **Seller:** [SMART INSIGHT](https://www.g2.com/sellers/smart-insight) - **HQ Location:** N/A - **LinkedIn® Page:** https://www.linkedin.com/company/No-Linkedin-Presence-Added-Intentionally-By-DataOps (1 employees on LinkedIn®) ### 20. [Paradime](https://www.g2.com/products/paradime/reviews) Paradime is a platform that offers a range of services, including seamless integration with various tools, in-app chat and email support **Who Is the Company Behind Paradime?** - **Seller:** [Paradime](https://www.g2.com/sellers/paradime) - **Year Founded:** 2020 - **HQ Location:** San Francisco, US - **Twitter:** @paradimelabs (131 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/paradimelabs/?originalSubdomain=uk (13 employees on LinkedIn®) ### 21. [Precisely Connect](https://www.g2.com/products/precisely-connect/reviews) Enable real time decisions with Precisely Connect. Seamlessly integrate data from legacy systems into modern cloud and data platforms for faster, more confident action. **Average Rating:** 4.5/5.0 **Total Reviews:** 1 **How Do G2 Users Rate Precisely Connect?** - **Quality of Support:** 8.3/10 (Category avg: 8.9/10) - **Ease of Use:** 10.0/10 (Category avg: 8.8/10) **Who Is the Company Behind Precisely Connect?** - **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% Enterprise #### What Are Recent G2 Reviews of Precisely Connect? **"[Easy to Learn, Quick to Build](https://www.g2.com/survey_responses/precisely-connect-review-12605025)"** **Rating:** 4.5/5.0 stars *— Verified User in Banking* [Read full review](https://www.g2.com/survey_responses/precisely-connect-review-12605025) --- ### 22. [RisingWave](https://www.g2.com/products/risingwave/reviews) RisingWave is an open-source distributed SQL streaming database designed for the cloud.It is designed to reduce the complexity and cost of building real-time applications. RisingWave consumes streaming data, performs incremental computations when new data comes in, and updates results dynamically. As a database system, RisingWave maintains results in its own storage so that users can access data efficiently. For more details about RisingWave, see https://risingwave.com/. **Who Is the Company Behind RisingWave?** - **Seller:** [RisingWave Labs](https://www.g2.com/sellers/risingwave-labs) - **Year Founded:** 2021 - **HQ Location:** San Francisco, US - **Twitter:** @RisingWaveLabs (3,173 Twitter followers) - **LinkedIn® Page:** https://linkedin.com/company/risingwave-labs (46 employees on LinkedIn®) ### 23. [Shakudo](https://www.g2.com/products/shakudo/reviews) Shakudo ensures compatibility across data tools allowing companies to build the best data infrastructure for their needs. With Shakudo you can mix and match your data tooling to create a more reliable, performant, and cost-effective stack than ever before. **Average Rating:** 4.5/5.0 **Total Reviews:** 2 **How Do G2 Users Rate Shakudo?** - **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 Shakudo?** - **Seller:** [Shakudo](https://www.g2.com/sellers/shakudo) - **Year Founded:** 2021 - **HQ Location:** Toronto, CA - **LinkedIn® Page:** https://ca.linkedin.com/company/shakudo (34 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 50% Mid-Market, 50% Small-Business #### What Are Shakudo's Pros and Cons? **Pros:** - Connectivity (1 reviews) - Data Access (1 reviews) - Data Integration (1 reviews) - Data Management (1 reviews) - Data Pipelining (1 reviews) **Cons:** - Data Management Issues (1 reviews) - Feature Limitations (1 reviews) - Lacking Features (1 reviews) - Lack of Functionality (1 reviews) - Lack of Tools (1 reviews) ### What Do G2 Reviewers Say About Shakudo? *AI-generated summary from verified user reviews* **Pros:** - Users find Shakudo's **connectivity** exceptional for integrating various data tools and optimizing their data stack. - Users find **data access seamless** with Shakudo, allowing optimal integration of various tools in their data stack. - Users appreciate how Shakudo's **data integration** effortlessly connects various tools, optimizing their data stack experience. - Users find Shakudo's **data management capabilities** invaluable for integrating various tools in their data stack. - Users value Shakudo for its ability to **seamlessly coordinate various data tools** in their data pipeline workflows. **Cons:** - Users note limited **data transformation capabilities** in Shakudo, often relying on other tools for complex data tasks. - Users note the **limited data transformation capabilities** of Shakudo, often requiring additional tools for complex tasks. - Users find the **lack of data transformation capabilities** limits their ability to perform complex data manipulations efficiently. - Users notice a **lack of functionality** in Shakudo, requiring additional tools for complex data manipulation tasks. - Users find a **lack of data transformation tools** in Shakudo, relying on other tools for complex tasks. #### What Are Recent G2 Reviews of Shakudo? **"[Designing an efficient infrastructure](https://www.g2.com/survey_responses/shakudo-review-9996719)"** **Rating:** 4.5/5.0 stars *— Eliyev E.* [Read full review](https://www.g2.com/survey_responses/shakudo-review-9996719) --- **"[P](https://www.g2.com/survey_responses/shakudo-review-9985567)"** **Rating:** 4.5/5.0 stars *— Giorgi B.* [Read full review](https://www.g2.com/survey_responses/shakudo-review-9985567) --- ### 24. [Stacksync](https://www.g2.com/products/stacksync/reviews) Stacksync is a no-code SaaS platform for data integration and workflow automation. Sync your tools bi-directionally in real-time, automate complex workflows, and monitor data pipelines effortlessly. Stacksync is cloud-deployed, zero-maintenance, and automatically handles essential operational tasks like security key rotation and rate limit management. Business teams leverage Stacksync to automate sales and marketing operations, while data teams use Stacksync to deliver ETL and reverse ETL pipelines in days — not weeks. **Who Is the Company Behind Stacksync?** - **Seller:** [Stacksync](https://www.g2.com/sellers/stacksync) - **Year Founded:** 2022 - **HQ Location:** 1007 Orange St 2611, 4th Floor, Wilmington, DE 19801, United States - **Twitter:** @stacksyncdata (117 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/stacksyncdata/ (10 employees on LinkedIn®) ### 25. [Strategy Mosaic](https://www.g2.com/products/strategy-mosaic/reviews) Strategy Mosaic, from Strategy (formerly MicroStrategy), is an enterprise-grade universal semantic layer solution designed to enhance the capabilities of AI and Business Intelligence (BI) within organizations. It addresses critical challenges such as data fragmentation and inconsistent metrics, which lead to untrusted AI answers, compliance risks, and runaway cloud costs. The universal semantic layer that Mosaic provides serves as a centralized repository for business definitions, hierarchies, and security rules, ensuring that all users access consistent metrics and KPIs regardless of the tools they employ. This single source of truth is actively monitored by our integrated Sentinel layer, which moves you from reactive audits to proactive, real-time governance. Sentinel provides immediate intelligence on potential data breaches, compliance risks, and cost-saving opportunities, helping you optimize cloud spend and prevent violations before they happen. Additionally, Mosaic empowers organizations to build an auditable foundation for AI. By providing a layer of rich business context and consistent, human-readable definitions, Mosaic gives AI models the deep understanding required to provide more accurate and verifiable answers. This accelerates time to insight, allows you to end vendor lock-in, and dramatically reduces the total cost of ownership (TCO) by eliminating costly data rework and optimizing data management processes. In summary, Strategy Mosaic stands out by addressing the fundamental issues of data fragmentation and governance. Its robust connectivity, centralized semantic layer, and focus on delivering trusted data make it an invaluable tool for organizations aiming to enhance their analytics capabilities and leverage AI effectively. **Average Rating:** 4.5/5.0 **Total Reviews:** 15 **How Do G2 Users Rate Strategy Mosaic?** - **Has the product been a good partner in doing business?:** 9.1/10 (Category avg: 8.9/10) - **Quality of Support:** 8.8/10 (Category avg: 8.9/10) - **Ease of Use:** 8.6/10 (Category avg: 8.8/10) - **Ease of Admin:** 8.7/10 (Category avg: 8.5/10) **Who Is the Company Behind Strategy Mosaic?** - **Seller:** [Strategy (formerly MicroStrategy)](https://www.g2.com/sellers/strategy-formerly-microstrategy) - **Company Website:** https://www.strategy.com/software - **Year Founded:** 1989 - **HQ Location:** Tysons Corner, VA - **Twitter:** @MicroStrategy (303,456 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/strategy/ (3,457 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 53% Enterprise, 40% Mid-Market #### What Are Strategy Mosaic's Pros and Cons? **Pros:** - Ease of Use (2 reviews) - Features (2 reviews) - Reporting (2 reviews) - Data Analysis (1 reviews) - Data Modeling (1 reviews) **Cons:** - Bugs (2 reviews) - Bug Issues (1 reviews) - Debugging Issues (1 reviews) - Expensive (1 reviews) - Learning Curve (1 reviews) ### What Do G2 Reviewers Say About Strategy Mosaic? *AI-generated summary from verified user reviews* **Pros:** - Users enjoy the **ease of use** of Strategy Mosaic, transforming planning with simple collaboration and intuitive visualizations. - Users value the **easy collaboration and AI-driven insights** in Strategy Mosaic that streamline planning and execution seamlessly. - Users value the **semantic layer** of Strategy Mosaic, appreciating its user-friendly, reliable data analytics across multiple carriers. - Users appreciate the **robust data analysis capabilities** of Strategy Mosaic, ensuring reliable insights from vast datasets. - Users value the **auto-magical experience** of creating initial data models effortlessly with Strategy Mosaic. **Cons:** - Users report **minor bugs** in Strategy Mosaic that hinder functionalities like cube publishing and mistake corrections. - Users experience frustrating **bug issues** with Strategy Mosaic that hinder effective error correction and usage. - Users often face **debugging issues** , finding that corrections do not modify the code as expected. - Users feel the cost of Strategy Mosaic is **high** , suggesting a need for better pricing options or licenses. - Users find the initial **learning curve of Strategy Mosaic** slightly overwhelming, though it improves with familiarity. #### What Are Recent G2 Reviews of Strategy Mosaic? **"[Strategy Mosaic Makes Strategic Planning Clear, Visual, and Team-Aligned](https://www.g2.com/survey_responses/strategy-mosaic-review-12611240)"** **Rating:** 4.0/5.0 stars *— Akash A.* [Read full review](https://www.g2.com/survey_responses/strategy-mosaic-review-12611240) --- **"[Effortless Planning and Team Alignment Made Simple](https://www.g2.com/survey_responses/strategy-mosaic-review-12008071)"** **Rating:** 4.5/5.0 stars *— Aditya K.* [Read full review](https://www.g2.com/survey_responses/strategy-mosaic-review-12008071) --- ## 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.