What is Faust?
It is a stream processing library, porting the ideas from Kafka Streams to Python. It provides both stream processing and event processing, sharing similarity with tools such as Kafka Streams, Apache Spark/Storm/Samza/Flink.
Faust is a tool in the Stream Processing category of a tech stack.
Faust is an open source tool with 6.7K GitHub stars and 536 GitHub forks. Here’s a link to Faust's open source repository on GitHub
Who uses Faust?
Companies
Developers
24 developers on StackShare have stated that they use Faust.
Faust Integrations
Python, Django, Flask, NumPy, and Pandas are some of the popular tools that integrate with Faust. Here's a list of all 8 tools that integrate with Faust.
Faust's Features
- Stream processing
- Event processing
- Build high performance distributed systems
- Real-time data pipelines
Faust Alternatives & Comparisons
What are some alternatives to Faust?
Kafka
Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
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.
Celery
Celery is an asynchronous task queue/job queue based on distributed message passing. It is focused on real-time operation, but supports scheduling as well.
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.
JUCE
It is a C++ framework for low-latency applications, with cross-platform GUI libraries to get your apps running on Mac OS X, Windows, Linux, iOS and Android.
