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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.
Log Compaction – Highlights in the Apache Kafka and Stream Processing Community – February 2017
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 […]
Confluent Delivers Upgrades to Clients, The streams API in Kafka, Brokers and Apache Kafka™ 0.10.1.1
Last November, we released Confluent 3.1, with new connectors, clients, and Enterprise features. Today, we’re pleased to announce Confluent 3.1.2, a patch release which incorporates the latest stable version of […]
Apache Kafka: Getting Started
Seems that many engineers have “Learn Kafka” on their new year resolution list. This isn’t very surprising. Apache Kafka is a popular technology with many use-cases. Armed with basic Kafka […]
Log Compaction: Highlights in the Apache Kafka and Stream Processing Community – January 2017
Happy 2017! Wishing you a wonderful year full of fast and scalable data streams. Many things have happened since we last shared the state of Apache Kafka® and the streams […]
The Data Dichotomy: Rethinking the Way We Treat Data and Services
If you were to stumble upon the whole microservices thing, without any prior context, you’d be forgiven for thinking it a little strange. Taking an application and splitting it into fragments, […]
Enterprise Streaming Multi-Datacenter Replication using Apache Kafka
One of the most common pain points we hear is around managing the flow and placement of data between datacenters. Almost every Apache Kafka user eventually ends up with clusters […]
Log Compaction | Highlights in the Apache Kafka and Stream Processing Community | December 2016
This month saw the proposal of a few KIPs which will have a big impact on Apache Kafka’s semantics as well as Kafka’s operability. KIP-95 : Incremental Batch Processing for […]
Announcing the 2017 Kafka Summits!
This year, we were pleased to host the inaugural Kafka Summit, the first global summit for the Apache Kafka community. Kafka Summit 2016 contributed valuable content to help Kafka users […]
Announcing the Availability of Confluent Platform in Azure Marketplace
Confluent and Microsoft are pleased to announce the successful integration of Confluent Platform into Microsoft’s Azure Marketplace. Users can now rapidly deploy a complete Confluent Platform cluster with the click […]
Announcing Confluent 3.1 with Apache Kafka 0.10.1.0
Today, we are excited to announce the release of Confluent 3.1, the only stream processing platform built entirely on Apache Kafka. At Confluent, our vision is to not only ship […]
Log Compaction | Highlights in the Apache Kafka and Stream Processing Community | November 2016
Last month the Apache Kafka community released version 0.10.1.0, the announcement blog contains a good description of new features and major improvements. In other exciting news, the PMC for Apache […]
Confluent Contributions to the Apache Kafka™ Client Ecosystem
If you are using Apache Kafka from a language other than Java one of the first questions you probably have is something like, “Why are there two (or five!) clients […]
Unifying Stream Processing and Interactive Queries in Apache Kafka
This post was co-written with Damian Guy, Engineer at Confluent, Michael Noll, Product Manager at Confluent and Neha Narkhede, CTO and Co-Founder at Confluent. We are excited to announce Interactive […]
Confluent Event Streaming Platform and Syncsort Data Management: Bringing Big Data to Life
I talk to a lot of folks in the big data industry about the challenges they’re tackling with big data technology. I’m endlessly fascinated with how each company chooses a unique architecture based on their distinctive needs, and yet, there are always patterns in the chaos...