Apache Samza
In today's world, Apache Samza is a topic that has captured the attention of millions of people around the world. Whether due to its historical relevance, its impact on current society, or its influence on popular culture, Apache Samza is a phenomenon that has generated debate, admiration and controversy. In this article, we will explore the different facets of Apache Samza, analyzing its importance in different areas and examining how it has evolved over time. From its appearance on the public scene to its multiple interpretations, Apache Samza is a topic that leaves no one indifferent, and its relevance remains palpable today.
| Apache Samza | |
|---|---|
 | |
| Original author | |
| Developer | Apache Software Foundation |
| Stable release | 1.8.0
/ 17 January 2023[1] |
| Repository | Samza Repository |
| Written in | Scala, Java |
| Operating system | Cross-platform |
| Type | Distributed stream processing |
| License | Apache License 2.0 |
| Website | samza |
Apache Samza is an open-source, near-realtime, asynchronous computational framework for stream processing developed by the Apache Software Foundation in Scala and Java. It has been developed in conjunction with Apache Kafka. Both were originally developed by LinkedIn.[2]
Overview
Samza allows users to build stateful applications that process data in real-time from multiple sources including Apache Kafka.
Samza provides fault tolerance, isolation and stateful processing. Unlike batch systems such as Apache Hadoop or Apache Spark, it provides continuous computation and output, which result in sub-second[3] response times.
There are many players in the field of real-time stream processing and Samza is one of the mature products.[4][5][6] It was added to Apache in 2013.[7]
Samza is used by multiple companies.[8] The biggest installation is in LinkedIn.
See also
- Apache Beam
- Druid (open-source data store)
- List of Apache Software Foundation projects
- Storm (event processor)
References
- ^ "Announcing the release of Apache Samza 1.8.0". Retrieved 28 March 2024.
- ^ "How LinkedIn Uses Apache Samza". InfoQ. Retrieved 2016-09-28.
- ^ "Samza: Stateful Scalable Stream Processing at LinkedIn" (PDF).
- ^ "Spark Streaming vs Flink vs Storm vs Kafka Streams vs Samza : Choose Your Stream Processing Framework". www.linkedin.com. Retrieved 2019-07-23.
- ^ "Comparing Apache Spark, Storm, Flink and Samza stream processing engines - Part 1". Scott Logic. Retrieved 2019-07-23.
- ^ "Hadoop, Storm, Samza, Spark, and Flink: Big Data Frameworks Compared". DigitalOcean. Retrieved 2019-07-23.
- ^ "Apache Samza". blogs.apache.org. Archived from the original on November 15, 2013. Retrieved 2019-07-23.
- ^ "Samza - Powered By". samza.apache.org. Retrieved 2019-07-23.
