Relationship to Kafka Streams

ksqlDB is the streaming database for Apache Kafka®. With ksqlDB, you can write event streaming applications by using a lightweight SQL syntax.

Kafka Streams is the Kafka library for writing streaming applications and microservices in Java and Scala.

ksqlDB is built on Kafka Streams, a robust stream processing framework that is part of Kafka.

ksqlDB gives you a query layer for building event streaming applications on Kafka topics. ksqlDB abstracts away much of the complex programming that's required for real-time operations on streams of data, so that one line of SQL can do the work of a dozen lines of Java or Scala.

For example, to implement simple fraud-detection logic on a Kafka topic named payments, you could write one line of SQL:

CREATE STREAM fraudulent_payments AS
 SELECT fraudProbability(data) FROM payments
 WHERE fraudProbability(data) > 0.8
 EMIT CHANGES;

The equivalent Scala code on Kafka Streams might resemble:

// Example fraud-detection logic using the Kafka Streams API.
object FraudFilteringApplication extends App {

  val builder: StreamsBuilder = new StreamsBuilder()
  val fraudulentPayments: KStream[String, Payment] = builder
    .stream[String, Payment]("payments-kafka-topic")
    .filter((_ ,payment) => payment.fraudProbability > 0.8)
  fraudulentPayments.to("fraudulent-payments-topic")

  val config = new java.util.Properties 
  config.put(StreamsConfig.APPLICATION_ID_CONFIG, "fraud-filtering-app")
  config.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, "kafka-broker1:9092")

  val streams: KafkaStreams = new KafkaStreams(builder.build(), config)
  streams.start()
}

ksqlDB is easier to use, and Kafka Streams is more flexible. Which technology you choose for your real-time streaming applications depends on a number of considerations. Keep in mind that you can use both ksqlDB and Kafka Streams together in your implementations.

Differences Between ksqlDB and Kafka Streams

The following table summarizes some of the differences between ksqlDB and Kafka Streams.

Differences	ksqlDB	Kafka Streams
You write:	SQL statements	JVM applications
Graphical UI	Yes, in Confluent Control Center and Confluent Cloud	No
Console	Yes	No
Data formats	Avro, Protobuf, JSON, JSON_SR, CSV	Any data format, including Avro, JSON, CSV, Protobuf, XML
REST API included	Yes	No, but you can implement your own
Runtime included	Yes, the ksqlDB server	Applications run as standard JVM processes
Queryable state	No	Yes

Developer Workflows

There are different workflows for ksqlDB and Kafka Streams when you develop streaming applications.

• ksqlDB: You write SQL queries interactively and view the results in real-time, either in the ksqlDB CLI or in Confluent Control Center.
• Kafka Streams: You write code in Java or Scala, recompile, and run and test the application in an IDE, like IntelliJ. You deploy the application to production as a jar file that runs in a Kafka cluster.

ksqlDB and Kafka Streams: Where to Start?

Use the following table to help you decide between ksqlDB and Kafka Streams as a starting point for your real-time streaming application development.

Start with ksqlDB when...	Start with Kafka Streams when...
New to streaming and Kafka	Prefer writing and deploying JVM applications like Java and Scala; for example, due to people skills, tech environment
To quicken and broaden the adoption and value of Kafka in your organization	Use case is not naturally expressible through SQL, for example, finite state machines
Prefer an interactive experience with UI and CLI	Building microservices
Prefer SQL to writing code in Java or Scala	Must integrate with external services, or use 3rd-party libraries (but ksqlDB user defined functions(UDFs) may help)
Use cases include enriching data; joining data sources; filtering, transforming, and masking data; identifying anomalous events	To customize or fine-tune a use case, for example, with the Kafka Streams Processor API: custom join variants, or probabilistic counting at very large scale with Count-Min Sketch
Use case is naturally expressible by using SQL, with optional help from UDFs	Need queryable state, which ksqlDB doesn't support
Want the power of Kafka Streams but you aren't on the JVM: use the ksqlDB REST API from Python, Go, C#, JavaScript, shell

Usually, ksqlDB isn't a good fit for BI reports, ad-hoc querying, or queries with random access patterns, because it's a continuous query system on data streams.

To get started with ksqlDB, try the Tutorials and Examples.

To get started with Kafka Streams, try the Streams Quick Start.

Next Steps

• Write Streaming Queries Against Apache Kafka® Using ksqlDB
• ksqlDB Developer Guide
• Streams Developer Guide

Page last revised on: 2020-04-29

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Last update: 2020-04-29