Kafka Streams

What is Kafka Streams?

Kafka Streams is an open-source stream processing library developed by Apache Software Foundation. It is designed to allow for building real-time applications and microservices without the need for a separate processing cluster. Kafka Streams offers a high-level stream DSL, low-level Processor API, and interactive queries to allow developers to process data efficiently.


Apache Kafka was originally developed by LinkedIn before being donated to the Apache Software Foundation in 2011, and became a top-level Apache project in 2012. Kafka Streams was added as a part of Apache Kafka in 2016, introduced in the version.

Functionality and Features

Kafka Streams provides several features that enable data transformation and processing:

  • Stream DSL: A high-level declarative API for processing data streams.
  • Processor API: A lower-level imperative API for processing data streams.
  • State Stores: Local storage associated with a stream task.
  • Interactive Queries: Allows querying of state stores in a stream application.


Kafka Streams applications run as individual instances, possibly spread across multiple machines. These instances can be elastically added or removed, allowing for workloads to be scaled effectively. Each instance processes records from one or more Kafka topics, and writes resulting records to one or more topics.

Benefits and Use Cases

Kafka Streams is used in a variety of industries for diverse use cases including real-time analytics, anomaly detection, and transforming data. Benefits include:

  • It is fully integrated with the rest of Apache Kafka.
  • It allows developers to work with a single, comprehensive system for event processing.
  • It provides a lightweight way to perform complex data processing tasks.

Challenges and Limitations

While Kafka Streams has a lot of benefits, there are also some limitations, such as lack of native support for complex event processing and windows-based processing or lack of built-in machine learning capabilities.

Integration with Data Lakehouse

Kafka Streams can be an effective way to feed real-time data into a lakehouse architecture, an integrated data management platform that combines the features of a traditional data warehouse and a modern data lake. This enables the lakehouse to have updated data for real-time business decisions.

Security Aspects

In terms of security, Kafka Streams supports the security features offered by Apache Kafka, including SSL/TLS, SASL, and pluggable Authorizer.


Performance of Kafka Streams applications is largely dependent on the performance of the underlying Kafka cluster. However, Kafka Streams offers various configuration options to tune application performance as per the requirements.


What is Kafka Streams used for? Kafka Streams is used to build real-time applications and microservices, where the input and output data are stored in Kafka clusters.

How does Kafka Streams work? Kafka Streams API enables applications to process data in real-time, handling both the input and output data stored in Kafka clusters.

What is Kafka Streams DSL? Kafka's Streams DSL (Domain-Specific Language) is a high-level API for stream processing.

What is the difference between Kafka and Kafka Streams? Kafka is a distributed streaming platform, whereas Kafka Streams is a client library for building applications and microservices that process data in real-time.

Does Kafka Streams support windowed computations? Yes, Kafka Streams supports windowed computations and aggregations.


Stream Processing: A type of computing that applies operations to continuously streaming data.

Microservices: A software development technique where an application is structured as a collection of loosely coupled services.

Data Lakehouse: An open, standards-based unified data platform that combines the capabilities of a data warehouse and a data lake.

SSL/TLS: Security protocols used to establish an encrypted connection between a server and a client.

SASL: Simple Authentication and Security Layer, a framework for authentication and security in internet protocols.

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