Real-time Event Processing with Kafka
Deliver faster insights with event-based data for streaming analytics.
Modern Analytics and Applications Consume Data Constantly
Digital transformation has become a top concern for business leaders. No matter your industry, your business is fast becoming a data business, and real-time applications, embedded with the smarts of streaming analytics, are the face of change.
Streaming data helps make the perfect offer to a loyal customer, alerts a mechanic to an issue before failure, or detects a cyber threat before damage is done. Predictive analytics and real-time decision making need a constant supply of fresh data. Yesterday’s data is historical data. Combine it with right-now data for insightful action.
The StreamSets DataOps Advantage
StreamSets makes it easy to build pipelines that capture event-based data for streaming analytics and process it in-flight to fuel your real-time applications with DataOps.

Flexible Hybrid and Multi-cloud Architecture
Easily migrate your work to any data platform or cloud infrastructure.






How It Works
Rapid Ingestion
Designed for streaming data, StreamSets DataOps Platform supports the design patterns and execution engines you need to get the freshest data from all your sources into your real-time applications and event-driven architectures (EDA).
- Streaming data ingestion
- Edge data shipping
- Time series data
- Real-time APIs

Transformation in Flight
Read out of any system for real time and apply lightweight transformations to power streaming analytics in flight. Call out to machine learning services or model on the fly to classify data as it streams.

Operationalize and Scale
StreamSets DataOps Platform gives you one place to monitor and manage all your pipelines, with second-by-second visibility into data flows so you can operate your event-driven architectures with confidence. Data performance SLAs and security policies enforced at run-time ensure the safety and reliability of your data as it flows into your real-time applications.
