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...
Learn how the latest innovations in Kora enable us to introduce new Confluent Cloud Freight clusters, which can save you up to 90% at GBps+ scale. Confluent Cloud Freight clusters are now available in Early Access.
Learn how to contribute to open source Apache Kafka by writing Kafka Improvement Proposals (KIPs) that solve problems and add features! Read on for real examples.
In this blog post, we’re going to get back to basics and walk through how to get started using Apache Kafka with your Python applications. We will assume some basic […]
In his book Design Patterns Explained, Alan Shalloway compares his car to an umbrella. After all, he uses both to stay dry in the rain. The umbrella has an advantage […]
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 […]