Confluent Blog
Data Products, Data Contracts, and Change Data Capture
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...
Introducing Confluent Cloud Freight Clusters
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.
Contributing to Apache Kafka®: How to Write a KIP
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.
Bottled Water: Real-time integration of PostgreSQL and Kafka
Summary: Confluent is starting to explore the integration of databases with event streams. As part of the first step in this exploration, Martin Kleppmann has made a new open source […]
Real-time full-text search with Luwak and Samza
This is an edited transcript of a talk given by Alan Woodward and Martin Kleppmann at FOSDEM 2015. Traditionally, search works like this: you have a large corpus of documents, […]
A Comprehensive REST Proxy for Kafka
As part of Confluent Platform 1.0 released about a month ago, we included a new Kafka REST Proxy to allow more flexibility for developers and to significantly broaden the number […]
Apache Kafka 0.8.2.1 release
The Apache Kafka community just announced the 0.8.2.1 release. This is a a bug fix release and fixes 4 critical issues reported in the 0.8.2.0 release (the full list of […]
How to Choose the Number of Topics/Partitions in a Kafka Cluster?
Note For the latest, check out the blog posts Apache Kafka® Made Simple: A First Glimpse of a Kafka Without ZooKeeper and Apache Kafka Supports 200K Partitions Per Cluster.
Turning the database inside-out with Apache Samza
This is an edited and expanded transcript of a talk I gave at Strange Loop 2014. The video recording (embedded below) has been watched over 8,000 times. For those of […]
Why Avro for Kafka Data?
If you are getting started with Kafka one thing you’ll need to do is pick a data format. The most important thing to do is be consistent across your usage. […]
Announcing the Confluent Platform 1.0
We are very excited to announce general availability of Confluent Platform 1.0, a stream data platform powered by Apache Kafka, that enables high-throughput, scalable, reliable and low latency stream data […]
Putting Apache Kafka To Use: A Practical Guide to Building an Event Streaming Platform (Part 2)
This is the second part of our guide on streaming data and Apache Kafka. In part one I talked about the uses for real-time data streams and explained the concept of […]
Putting Apache Kafka To Use: A Practical Guide to Building an Event Streaming Platform (Part 1)
Data systems have mostly focused on the passive storage of data. Phrases like “data warehouse” or “data lake” or even the ubiquitous “data store” all evoke places data goes to […]
Stream Processing, CEP, Event Sourcing, and Data Streaming Explained
Some people call it stream processing. Others call it event streaming, complex event processing (CEP), or CQRS event sourcing. Sometimes, such buzzwords are just smoke and mirrors, invented by companies […]
What’s coming in Apache Kafka 0.8.2
I am very excited to tell you about the forthcoming 0.8.2 release of Apache Kafka. Kafka is a fault-tolerant, low-latency, high-throughput distributed messaging system used in data pipelines at several […]
Announcing Confluent, a Company for Apache Kafka® and Realtime Data
Today I’m excited to announce that Neha Narkhede, Jun Rao, and I are forming a start-up called Confluent around realtime data and the open source project Apache Kafka® that we […]