Open-source software foundation Apache released version 1.0.0 of its Kafka distributed data streaming platform today, with the first full version number indicating Apache’s confidence that Kafka is ready for major professional use.
“Apache Kafka is playing a bigger role as companies are moving to real-time streaming and embracing stream processing,” Jun Rao, vice president of the Apache Kafka team, said in the announcement. “The 1.0.0 release is an important milestone for the Apache Kafka community as we’re committed to making it ready for enterprise adoption.”
The Apache Foundation highlighted features of Kafka 1.0.0 aimed at enterprises, like the ability to publish and subscribe to streams of data at a massive scale; real-time stream processing with exactly-once semantics, which avoids sending the same messages multiple times in the case of a connection error; and long-term storage of data streams.
Accompanying various bug fixes and general improvements in the update are performance improvements to Apache’s implementation of TLS and CRC32C, including Java 9 support, faster controlled shutdown, better JBOD support and exactly-once semantics.
As Apache describes it in its announcement, “Kafka provides low-latency, high-throughput, fault-tolerant publish-and-subscribe pipelines and is able to process streams of events. Kafka provides reliable, millisecond responses to support both customer-facing applications and connecting downstream systems with real-time data. Kafka is unique in that it can publish and subscribe to streams of data like a messaging system, process streams of data efficiently and in real time and store streams of data safely in a distributed, replicated cluster.”
Apache Kafka 1.0.0 will be demoed at the the upcoming Kafka Summit 2018 in London and San Francisco.
“We invite everyone to download Apache Kafka 1.0.0 and try it out,” Rao said. “We welcome community participation and look forward to engaging with users and hearing feedback at upcoming conferences and meetups as well as through the mailing list and pull requests.”