KSQL - Streaming SQL for Apache Kafka

KSQL is now GA and officially supported by Confluent Inc. Get started with KSQL today.

KSQL is the streaming SQL engine for Apache Kafka.

KSQL is an open source streaming SQL engine for Apache Kafka. It provides a simple and completely interactive SQL interface for stream processing on Kafka; no need to write code in a programming language such as Java or Python. KSQL is open-source (Apache 2.0 licensed), distributed, scalable, reliable, and real-time. It supports a wide range of powerful stream processing operations including aggregations, joins, windowing, sessionization, and much more.

Click here to watch a screencast of the KSQL demo on YouTube.

Getting Started and Download

Stable Releases

Stable releases are published every four months and are officially supported by Confluent.

Download latest stable KSQL, which is included in the Enterprise and Open Source editions of Confluent Platform.
Follow the Quick Start.
Read the KSQL Documentation, notably the KSQL Tutorials and Examples, which include Docker-based variants.

Preview Releases

In addition to supported stable KSQL releases, we also provide monthly preview releases. We encourage you to try them in development and testing environments and to take advantage of Confluent Community resources to get help and share feedback.

Download latest KSQL Preview.
Follow the Preview Quick Start.
Read the KSQL Preview Documentation, notably KSQL Tutorials and Examples, which include Docker-based variants.

Documentation

See KSQL documentation for the latest stable release.

Use Cases and Examples

Streaming ETL

Apache Kafka is a popular choice for powering data pipelines. KSQL makes it simple to transform data within the pipeline, readying messages to cleanly land in another system.

CREATE STREAM vip_actions AS
  SELECT userid, page, action
  FROM clickstream c
  LEFT JOIN users u ON c.userid = u.user_id
  WHERE u.level = 'Platinum';

Anomaly Detection

KSQL is a good fit for identifying patterns or anomalies on real-time data. By processing the stream as data arrives you can identify and properly surface out of the ordinary events with millisecond latency.

CREATE TABLE possible_fraud AS
  SELECT card_number, count(*)
  FROM authorization_attempts
  WINDOW TUMBLING (SIZE 5 SECONDS)
  GROUP BY card_number
  HAVING count(*) > 3;

Monitoring

Kafka's ability to provide scalable ordered messages with stream processing make it a common solution for log data monitoring and alerting. KSQL lends a familiar syntax for tracking, understanding, and managing alerts.

CREATE TABLE error_counts AS
  SELECT error_code, count(*)
  FROM monitoring_stream
  WINDOW TUMBLING (SIZE 1 MINUTE)
  WHERE  type = 'ERROR'
  GROUP BY error_code;

Latest News

KSQL April 2018 Preview Release available, May 2018
Confluent Platform 4.1 with Production-Ready KSQL Now Available, Apr 2018
Press Release: KSQL GA announced for early April 2018
We ❤ syslogs: Real-time syslog Processing with Apache Kafka and KSQL—Part 2: Event-Driven Alerting with Slack, Apr 2018
We ❤ syslogs: Real-time syslog Processing with Apache Kafka and KSQL—Part 1: Filtering, Apr 2018
KSQL in Action: Enriching CSV Events with Data from RDBMS into AWS, Mar 2018
KSQL February 2018 Preview Release available -- bug fixes, performance and stability improvements
Secure Stream Processing with Apache Kafka, Confluent Platform and KSQL, Feb 2018 -- stream processing examples using KSQL that show how companies are using Apache Kafka to grow their business and to analyze data in real time; how to secure KSQL and the entire Confluent Platform with encryption, authentication, and authorization
KSQL in Action: Real-Time Streaming ETL from Oracle Transactional Data, Feb 2018 -- replacing batch extracts with event streams, and batch transformation with in-flight transformation; we take a stream of data from a transactional system built on Oracle, transform it, and stream the results into Elasticsearch
KSQL January 2018 Preview Release available -- improved data exploration with PRINT TOPIC, SHOW TOPICS; improved analytics with TOPK, TOPKDISTINCT aggregations; operational improvements (command line tooling for metrics); distributed failure testing in place
KSQL December 2017 Preview Release available -- support for Avro and Confluent Schema Registry; easy data conversion between Avro, JSON, Delimited data; joining streams and tables across different data formats; operational improvements (DESCRIBE EXTENDED, EXPLAIN, and new metrics); optimizations (faster server startup and recovery times, better resource utilization)

Join the Community

You can get help, learn how to contribute to KSQL, and find the latest news by connecting with the Confluent community.

Ask a question in the #ksql channel in our public Confluent Community Slack. Account registration is free and self-service.
Join the Confluent Google group.

Contributing

Contributions to the code, examples, documentation, etc. are very much appreciated.

Report issues and bugs directly in this GitHub project.
Learn how to work with the KSQL source code, including building and testing KSQL as well as contributing code changes to KSQL by reading our Development and Contribution guidelines.

License

The project is licensed under the Apache License, version 2.0.

Apache, Apache Kafka, Kafka, and associated open source project names are trademarks of the Apache Software Foundation.

mrwanny/ksql