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What is KSQL?

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.
KSQL is a tool in the Stream Processing category of a tech stack.
KSQL is an open source tool with 5.9K GitHub stars and 1K GitHub forks. Here’s a link to KSQL's open source repository on GitHub

Who uses KSQL?

10 companies reportedly use KSQL in their tech stacks, including Voicebridge, Doodle, and Data Engineering.

42 developers on StackShare have stated that they use KSQL.

KSQL Integrations

Pros of KSQL
Streamprocessing on Kafka
SQL syntax with windowing functions over streams
Easy transistion for SQL Devs
Decisions about KSQL

Here are some stack decisions, common use cases and reviews by companies and developers who chose KSQL in their tech stack.

Needs advice
ConfluentConfluentKafka StreamsKafka Streams

I have recently started using Confluent/Kafka cloud. We want to do some stream processing. As I was going through Kafka I came across Kafka Streams and KSQL. Both seem to be A good fit for stream processing. But I could not understand which one should be used and one has any advantage over another. We will be using Confluent/Kafka Managed Cloud Instance. In near future, our Producers and Consumers are running on premise and we will be interacting with Confluent Cloud.

Also, Confluent Cloud Kafka has a primitive interface; is there any better UI interface to manage Kafka Cloud Cluster?

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KSQL's Features

  • Real-time
  • Kafka-native
  • Simple constructs for building streaming apps

KSQL Alternatives & Comparisons

What are some alternatives to KSQL?
Apache Spark
Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
Kafka Streams
It is a client library for building applications and microservices, where the input and output data are stored in Kafka clusters. 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.
Apache Storm
Apache Storm is a free and open source distributed realtime computation system. Storm makes it easy to reliably process unbounded streams of data, doing for realtime processing what Hadoop did for batch processing. Storm has many use cases: realtime analytics, online machine learning, continuous computation, distributed RPC, ETL, and more. Storm is fast: a benchmark clocked it at over a million tuples processed per second per node. It is scalable, fault-tolerant, guarantees your data will be processed, and is easy to set up and operate.
Apache Flink
Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.
It delivers the only complete open source middleware platform. With its revolutionary componentized design, it is also the only open source platform-as-a-service for private and public clouds available today. With it, seamless migration and integration between servers, private clouds, and public clouds is now a reality.
See all alternatives

KSQL's Followers
125 developers follow KSQL to keep up with related blogs and decisions.