Kafka in the Cloud: Why it’s 10x better with Confluent | Find out more
Change data capture is a popular method to connect database tables to data streams, but it comes with drawbacks. The next evolution of the CDC pattern, first-class data products, provide resilient pipelines that support both real-time and batch processing while isolating upstream systems...
Check out all the highlights from the Apache Flink® 1.19 release!
Apache Kafka 3.7 introduces updates to the Consumer rebalance protocol, an official Apache Kafka Docker image, JBOD support in Kraft-based clusters, and more!
For many, microservices are built on a protocol of requests and responses. REST etc. This approach is very natural. It is after all the way we write programs: we make […]
We are very excited to share a wealth of streaming news from the past month! If you are looking for an ideal streaming data service that delivers the resilient, scalable […]
Introduction What’s great about the Kafka Streams API is not just how fast your application can process data with it, but also how fast you can get up and running […]
Apache Kafka® is the best enterprise streaming platform that runs straight off the shelf. Just point your client applications at your Kafka cluster and Kafka takes care of the rest: […]
Today, I’m really excited to announce Confluent CloudTM, Apache Kafka® as a Service: the simplest, fastest, most robust and cost effective way to run Apache Kafka in the public cloud. […]
In Q1, Confluent conducted a survey of the Apache Kafka® community and those using streaming platforms to learn about their application of streaming data. This is our second execution of […]
The Google Dataflow team has done a fantastic job in evangelizing their model of handling time for stream processing. Their key observation is that in most cases you can’t globally […]
Here at Confluent, our goal is to ensure every company is successful with their streaming platform deployments. Oftentimes, we’re asked to come in and provide guidance and tips as developers […]
Pandora began adoption of Apache Kafka® in 2016 to orient its infrastructure around real-time stream processing analytics. As a data-driven company, we have a several thousand node Hadoop clusters with hundreds of Hive tables critical to Pandora’s operational and reporting success...
Note: The blog post Ensure Data Quality and Data Evolvability with a Secured Schema Registry contains more recent information. If you use Apache Kafka to integrate and decouple different data […]
Big news this month! First and foremost, Confluent Platform 3.2.0 with Apache Kafka® 0.10.2.0 was released! Read about the new features, check out all 200 bug fixes and performance improvements […]
We’re excited to announce the release of Confluent 3.2, our enterprise streaming platform built on Apache Kafka. At Confluent, our vision is to provide a comprehensive, enterprise-ready streaming platform that […]
At the end of 2016 we conducted a survey of the Apache Kafka® community regarding their use of Kafka clients (the producers and consumers used with Kafka) and their priorities […]
As always, we bring you news, updates and recommended content from the hectic world of Apache Kafka® and stream processing. Sometimes it seems that in Apache Kafka every improvement is […]