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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.
IBM and Confluent Announce Strategic Partnership
I’m excited to announce a new strategic partnership with IBM. As part of this partnership, IBM will be reselling Confluent Platform, enabling its customers to leverage their existing IBM relationships […]
Digital Transformation in Style: How Boden Innovates Retail Using Apache Kafka
As a clothing retailer with more than 1.5 million customers worldwide, Boden is always looking to capitalise on business moments to drive sales. For example, when the Duchess of Cambridge […]
Analysing Historical and Live Data with ksqlDB and Elastic Cloud
Building data pipelines isn’t always straightforward. The gap between the shiny “hello world” examples of demos and the gritty reality of messy data and imperfect formats is sometimes all too […]
How Real-Time Stream Processing Safely Scales with ksqlDB, Animated
Software engineering memes are in vogue, and nothing is more fashionable than joking about how complicated distributed systems can be. Despite the ribbing, many people adopt them. Why? Distributed systems […]
Use Cases and Architectures for HTTP and REST APIs with Apache Kafka
This blog post presents the use cases and architectures of REST APIs and Confluent REST Proxy, and explores a new management API and improved integrations into Confluent Server and Confluent […]
Kafka Summit 2021 – Double the Fun
My own sense of the passage of time in 2020 is no sure guide, but honestly it seems like Kafka Summit just happened—yet here we are, deep into planning for […]
The Cloud-Native Evolution of Apache Kafka on Kubernetes
It’s almost KubeCon! Let’s talk about the state of cloud-native Apache Kafka® and other distributed systems on Kubernetes. Over the last decade, our industry has seen the rise of container […]
Advanced Testing Techniques for Spring for Apache Kafka
Asynchronous boundaries. Frameworks. Configuring frameworks. Apache Kafka®. All of these share one thing in common: complexity in testing. Now imagine them combined—it gets much harder. This is the final blog […]
Self-Describing Events and How They Reduce Code in Your Processors
Have you ever had to write a program that needed to handle any data payload that could be thrown at you? If so, did you always have to update the […]
Project Metamorphosis Month 7: Reliable Event Streaming with Confluent Cloud and Proactive Support
The rise of the cloud introduced a focus on rapid iteration and agility that is founded on specialization. If you are an application developer, you know your applications better than […]
How to Choose Between Strict and Dynamic Schemas
Event modeling has always been a pain point in organizations. From figuring out the standard format of your schemas, processing said data models effectively, and finally testing before you deploy […]
What’s New in Confluent Cloud Security
Note: Please see the blog post Introducing Cluster RBAC, Audit Logs, and BYOK for Enterprise-Grade Security for the latest updates.
Announcing Pull Queries in Preview in Confluent Cloud ksqlDB
“Persistent” queries have historically formed the basis of ksqlDB applications, which continuously transform, enrich, aggregate, materialize, and join your Apache Kafka® data using a familiar SQL interface. ksqlDB continuously executes […]
Building Streaming Data Architectures with Qlik Replicate and Apache Kafka
A fundamental challenge with today’s “data explosion” is finding the best answer to the question, “So where do I put my data?” while avoiding the longer-term problem of data warehouses, […]