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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.
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 […]
Apache Kafka for Real-Time Retail at Walmart Labs
This post is by Anil Kumar, Global eCommerce Engineer at Walmart Labs. Anil specializes in enabling stream processing, cloud computing, ad technology, search services, information retrieval, transport and application layer protocols, […]
Announcing Apache Kafka 0.10.1.0
The Apache Kafka community is pleased to announce the release of Apache Kafka 0.10.1.0. This is a feature release which includes the completion of 15 KIPs, over 200 bug fixes and […]
Streaming Data from Oracle using Oracle GoldenGate and the Connect API in Kafka
Note As of February 2021, Confluent has launched its own Oracle CDC connector. Read this blog post for the latest information.
Log Compaction | Highlights in the Apache Kafka and Stream Processing Community | October 2016
This month the community has been focused on the upcoming release of Apache Kafka 0.10.1.0. Led by the fearless release manager, Jason Gustafson, we voted on a release plan, cut […]
Introducing Apache Kafka™ for the Enterprise
In May, we introduced our first enterprise-focused feature, Confluent Control Center, with the 3.0 release of Confluent. Today, more than 35% of the Fortune 500 companies use Kafka for mission-critical […]
Want to migrate to AWS Cloud? Use Apache Kafka.
Amazon’s AWS cloud is doing really well. Doing well to the tune of making $2.57 Billion in Q1 2016. That’s 64% up from Q1 last year. Clearly a lot of […]
Log Compaction | Highlights in the Apache Kafka and Stream Processing Community | September 2016
It is September and it’s evident that everyone is back from their summer vacation! We released Apache Kafka 0.10.0.1 which includes fixes of the bugs in the 0.10.0 release. In […]
The Connect API in Kafka Cassandra Sink: The Perfect Match
The Connect API in Kafka is a scalable and robust framework for streaming data into and out of Apache Kafka, the engine powering modern streaming platforms. At DataMountaineer, we have worked on many big data and fast data projects across many industries from financial...
Event sourcing, CQRS, stream processing and Apache Kafka: What’s the connection?
Event sourcing as an application architecture pattern is rising in popularity. Event sourcing involves modeling the state changes made by applications as an immutable sequence or “log” of events. Instead […]
Announcing Confluent Platform 3.0.1 & Apache Kafka 0.10.0.1
A few months ago, we announced the release of open-source Confluent Platform 3.0 and Apache Kafka 0.10, marking the availability of Kafka Streams — the new stream processing engine of […]
Flink and Kafka Streams: a Comparison and Guideline for Users
This blog post is written jointly by Stephan Ewen, CTO of data Artisans, and Neha Narkhede, CTO of Confluent. Stephan Ewen is PMC member of Apache Flink and co-founder and CTO […]
Sharing is Caring: Multi-tenancy in Distributed Data Systems
Most people think that what’s exciting about distributed systems is the ability to support really big applications. When you read a blog about a new distributed database, it usually talks […]