StreamSets for Cloudera
Deliver continuous data for machine learning and advanced analytics in your Cloudera Data Hub pipeline
Simplify and Speed Data Ingestion to Cloudera
If you understand the logistic flow of data, you can build a data pipeline to Data Hub with StreamSets. Power your advanced analytics, machine learning, and ETL using a visual user interface to connect 100s of data sources to your Cloudera Data Hub cluster for comprehensive, large-scale analytics.
Native Integrations with Cloudera
Accelerate your advanced analytics on Cloudera with rapid data integration.
Uncover Value in Big Data with Cloudera
Detect and Respond to Data Drift
No other technology lets you get rapid value from your Data Hub. Only StreamSets Data Platform features smart data pipelines with built-in data drift detection and handling. Support for brokers like Kafka and Flume helps users get better reliability from open source engines.
Design for Batch, Streaming, and CDC
No need to design complex architectures. The StreamSets Data Platform helps you design ETL and stream processing jobs with a single design experience and execute in any engine in the Cloudera ecosystem. StreamSets helps users execute on the best engine for the job while giving visibility to all data movement across your clusters and connected data systems.
Harness the Power of Apache Spark, Minus the Complexity
StreamSets helps you rapidly build Apache Spark applications and ETL processes to deploy on your Data Hub. StreamSets also allows users to build self-service machine learning pipelines, deploy them into production, and monitor their health and performance as you scale.
Data Engineers Handbook for Snowflake
Design Considerations for Apache Spark Deployment
Ready to Get Started?
We’re here to help you start building pipelines or see the platform in action.