Big Data Integration Platforms Resources
Articles, Glossary Terms, Discussions, and Reports to expand your knowledge on Big Data Integration Platforms
Resource pages are designed to give you a cross-section of information we have on specific categories. You'll find articles from our experts, feature definitions, discussions from users like you, and reports from industry data.
Big Data Integration Platforms Articles
G2 Launches New Category for DataOps Platforms
Big Data Integration Platforms Glossary Terms
Big Data Integration Platforms Discussions
Hey all, we have been using Census for a while and I wanted to ask around how else are you using Census today? We are using Census mainly as a reverse ETL tool, but how else are you using Census today?
how do i sync data from Snowflake to Salesforce using Census.
Hey G2 community, I’m curious. What do you think are the best tools for managing big data integration across hybrid environments (a mix of on-premises and cloud)? I’m putting together a list of platforms that can handle complex pipelines, ensure governance, and keep performance strong when data lives in multiple places. If you’ve used any of these or have others you’d recommend, I’d love to hear your experience.
Azure Data Factory – Flexible Hybrid Integration
Azure Data Factory makes it easy to connect on-premises databases with cloud storage and analytics platforms. With built-in connectors and integration runtime options, it’s a solid choice for enterprises that need smooth orchestration between data centers and cloud systems.
IBM StreamSets – Real-Time Hybrid Pipelines
IBM StreamSets is designed for DataOps and hybrid data environments. It provides strong pipeline monitoring, governance, and support for streaming workloads, which is especially useful when data needs to move continuously across different environments.
AWS Glue – Serverless Hybrid Integration
AWS Glue offers serverless ETL and integration capabilities. While it’s cloud-native, it also supports hybrid setups by connecting on-premises data sources to AWS services, making it easier for teams to gradually move to the cloud.
Workato – Hybrid Integration + Automation
Workato combines integration with automation, helping organizations bridge SaaS applications with on-premises systems. Its low-code recipes make it possible to set up hybrid workflows without heavy engineering effort.
5X – Orchestration for Modern Hybrid Data Stacks
5X provides a managed framework to unify tools across a modern data stack. For teams running both cloud-based analytics and on-premises systems, it offers governance and monitoring that ensure hybrid environments remain well-orchestrated.
What do you think of these suggestions? Have you worked with one of these platforms (or another) that helped simplify hybrid data integration at scale? Which features—connectivity, governance, or real-time monitoring—mattered most for your team?
From what I’ve seen, Azure Data Factory is a go-to for hybrid pipelines in Microsoft-heavy shops, while IBM StreamSets seems stronger for real-time monitoring. I'm curious—has anyone tried Workato for hybrid use cases where automation is just as important as integration?


