How to: Data Stream Processing
* [Apache Beam](https://github.com/apache/beam) ![](https://img.shields.io/github/stars/apache/beam.svg?cacheSeconds=86400) Apache Beam is a unified programming model for Batch and Streaming.
* [Apache Flink](https://github.com/apache/flink) ![](https://img.shields.io/github/stars/apache/flink.svg?cacheSeconds=86400) - Open source stream processing framework with powerful stream and batch processing capabilities.
* [Apache Kafka](https://github.com/apache/kafka) ![](https://img.shields.io/github/stars/apache/kafka.svg?cacheSeconds=86400) - Kafka client library for building applications and microservices where the input and output are stored in kafka clusters.
* [Apache Samza](https://github.com/apache/samza) ![](https://img.shields.io/github/stars/apache/samza.svg?cacheSeconds=86400) - Distributed stream processing framework. It uses Apache Kafka for messaging, and Apache Hadoop YARN to provide fault tolerance, processor isolation, security, and resource management.
* [Apache Spark](https://github.com/apache/spark) ![](https://img.shields.io/github/stars/apache/spark.svg?cacheSeconds=86400) - Micro-batch processing for streams using the apache spark framework as a backend supporting stateful exactly-once semantics.
* [Bytewax](https://github.com/bytewax/bytewax) ![](https://img.shields.io/github/stars/bytewax/bytewax.svg?cacheSeconds=86400) - Flexible Python-centric stateful stream processing framework built on top of Rust engine.
* [FastStream](https://github.com/airtai/faststream) ![](https://img.shields.io/github/stars/airtai/faststream.svg?cacheSeconds=86400) - A modern broker-agnostic streaming Python framework supporting Apache Kafka, RabbitMQ and NATS protocols, inspired by FastAPI and easily integratable with other web frameworks.
* [MOA](https://github.com/Waikato/moa) ![](https://img.shields.io/github/stars/Waikato/moa.svg?cacheSeconds=86400) - MOA (Massive Online Analysis) is an open source framework for Big Data stream mining.
* [MosaicML Streaming](https://github.com/mosaicml/streaming) ![](https://img.shields.io/github/stars/mosaicml/streaming.svg?cacheSeconds=86400) - Fast, deterministic streaming of large datasets from cloud storage for distributed model training.
* [RisingWave](https://github.com/risingwavelabs/risingwave) ![](https://img.shields.io/github/stars/risingwavelabs/risingwave.svg?cacheSeconds=86400) - A distributed SQL streaming database that unifies stream processing and low-latency serving, ideal for building and serving features for online machine learning.
* [TensorStore](https://github.com/google/tensorstore) ![](https://img.shields.io/github/stars/google/tensorstore.svg?cacheSeconds=86400) - Library for reading and writing large multi-dimensional arrays.