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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 Data Integration Platform 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. 

Learn More
Kafka dataflows for real-time applications
Design Apache Kafka dataflows with a no code, visual interface
Automatically detect and respond to data drift to keep pipelines flowing
Build real-time data streams for analyzing events and predictive analytics

Flexible Hybrid and Multi-cloud Architecture

Easily migrate your work to any data platform or cloud infrastructure. 

Kafka dataflows for real-time applications
Kafka dataflows for Azure Event Hub real-time applications
Kafka dataflows for Amazon Kinesis real-time applications
Kafka dataflows for Databricks and real-time applications
Kafka dataflows for Hadoop real-time applications
Kafka dataflows for Google Cloud real-time applications

How It Works

Rapid Ingestion

Designed for streaming data, StreamSets 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
Rapid ingestion for real-time applications

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.

Transformation in flight for streaming analytics

Operationalize and Scale

StreamSets Data 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. 

Operationalize and scale real-time application data pipelines

Awards and Recognition

Top 50 IT Infrastructure Products G2 Badge

Frequently Asked Questions

What is Kafka?

Apache Kafka is an open-source distributed event streaming platform (also known as a “pub/sub” messaging system) that brokers communication between bare-metal servers, virtual machines, and cloud-native services. StreamSets supports Kafka as a source, broker, and destination allowing you to build complex Kafka pipelines with message brokering at every stage.

What is the difference between Kafka and Kafka Streams?

Kafka is the data streaming platform, while Kafka Streams is a client library for building applications and microservices, where the input and output data are stored in Kafka cluster. It combines the simplicity of writing and deploying standard Java and Scala applications on the client side with the benefits of Kafka's server-side cluster technology.

Whitepapers & Ebooks

Data Engineer’s Handbook: 4 Cloud Design Patterns

4 Cloud Design Patterns for Data Ingestion and Transformation

Real-time Analytics with AWS and StreamSets

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Eckerson Group | Getting Started with DataOps for Data Analytics Leaders

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