The Apache Software Foundation Announces Apache® Kafka® v1.0.0

Popular Open Source enterprise-grade scalable streaming platform in use at Capital One, Goldman Sachs, ING, LinkedIn, Netflix, Pinterest, Rabobank, Target, The New York Times, Uber, Yelp, and Zalando, among others.


Forest Hill, MD, Nov. 01, 2017 (GLOBE NEWSWIRE) -- The Apache Software Foundation (ASF), the all-volunteer developers, stewards, and incubators of more than 350 Open Source projects and initiatives, announced today the availability of Apache® Kafka® v1.0.0, the latest version of the Open Source distributed streaming platform.

Apache Kafka is capable of handling trillions of events per day, and provides a unified platform for handling real-time data feeds and scalable distributed applications. A single Kafka broker can handle hundreds of megabytes of reads and writes per second from thousands of clients.

"Apache Kafka is playing a bigger role as companies are moving to real-time streaming and embracing stream processing," said Jun Rao, Vice President of Apache Kafka. "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."

Initially conceived as a messaging queue, Kafka is based on an abstraction of a distributed commit log. 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.

The Apache Kafka 1.0.0 release includes performance improvements with exactly-once semantics, significantly faster TLS and CRC32C implementations with Java 9 support, significantly faster controlled shutdown, and better JBOD support, among other general improvements and bug fixes. This release represents a significant milestone as companies run Kafka at enterprise scale with the ability to:

  • Publish and subscribe to streams of data at massive scale
  • Process streams of data with state of the art real-time stream processing capabilities and exactly-once semantics
  • Store streams of data durably for the long term

Apache Kafka is in use at large and small companies worldwide, including Capital One, Goldman Sachs, ING, LinkedIn, Netflix, Pinterest, Rabobank, Target, The New York Times, Uber, Yelp, and Zalando, among others.

"We enjoy Kafka's great features and vibrant community. Kafka enabled us to process trillions of messages per day in a scalable way. This opened up a completely new frontier for us to efficiently process data in motion to help us better serve Netflix members around the world," said Allen Wang, Senior Software Engineer at Netflix.

"Yelp uses Apache Kafka to power everything from application logs to analytics, enabling us to more easily and efficiently connect people with great local businesses," said Justin Cunningham, Software Engineer at Yelp. "The 1.0 release is a major milestone, and we're thrilled that Apache Kafka has continuously added innovative new features, while enhancing the reliability and scalability that Yelp depends on as our mobile traffic grows."

"Apache Kafka is Uber's data platform that reliably delivers trillions of messages per day, and empowers the real-time business intelligence to serve all the users around the world," said Lei Lin, Engineer Manager at Uber. "It's very exciting to see the new milestone of Apache Kafka 1.0 release and we are looking forward to this release."

"We invite everyone to download Apache Kafka 1.0.0 and try it out," added Rao. "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."

Catch Apache Kafka in action at Kafka Summit 2018 in London and San Francisco https://kafka-summit.org/ , and at numerous local meetups https://kafka.apache.org/events .

Availability and Oversight
Apache Kafka software is released under the Apache License v2.0 and is overseen by a self-selected team of active contributors to the project. A Project Management Committee (PMC) guides the Project's day-to-day operations, including community development and product releases. For downloads, documentation, and ways to become involved with Apache Kafka, visit https://kafka.apache.org/ and https://twitter.com/apachekafka .

About The Apache Software Foundation (ASF)
Established in 1999, the all-volunteer Foundation oversees more than 350 leading Open Source projects, including Apache HTTP Server -- the world's most popular Web server software. Through the ASF's meritocratic process known as "The Apache Way," more than 680 individual Members and 6,300 Committers successfully collaborate to develop freely available enterprise-grade software, benefiting millions of users worldwide: thousands of software solutions are distributed under the Apache License; and the community actively participates in ASF mailing lists, mentoring initiatives, and ApacheCon, the Foundation's official user conference, trainings, and expo. The ASF is a US 501(c)(3) charitable organization, funded by individual donations and corporate sponsors including Alibaba Cloud Computing, ARM, Bloomberg, Budget Direct, Capital One, Cash Store, Cerner, Cloudera, Comcast, Confluent, Facebook, Google, Hortonworks, HP, Huawei, IBM, InMotion Hosting, iSigma, LeaseWeb, Microsoft, ODPi, PhoenixNAP, Pivotal, Private Internet Access, Produban, Red Hat, Serenata Flowers, Target, WANdisco, and Yahoo. For more information, visit http://www.apache.org/ and https://twitter.com/TheASF

© The Apache Software Foundation. "Apache", "Kafka", "Apache Kafka", and "ApacheCon" are registered trademarks or trademarks of the Apache Software Foundation in the United States and/or other countries. All other brands and trademarks are the property of their respective owners.

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