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Stream Processing
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.
Announcing ksqlDB 0.27.1
We are excited to announce the ksqlDB 0.27.1 release! This iteration brings forth new functionality for dynamic data access against multi-schema topics, a host of improvements relating to working with […]
Announcing ksqlDB 0.26
We are excited to bring forward yet another ksqlDB release with ksqlDB 0.26. This time we have focused on improving your experience with aggregate functions, JOINs, and schemas. We have […]
Stream Processing vs. Batch Processing: What to Know
With more data being produced in real time by many systems and devices than ever before, it is critical to be able to process it in real time and get […]
Announcing ksqlDB 0.25.1
We are thrilled to announce ksqlDB 0.25! It comes with a slew of improvements and new features. In particular, we improved how UDAFs work with complex types like Structs and […]
Introducing Stream Processing Use Case Recipes Powered by ksqlDB
From fraud detection and predictive analytics, to real-time customer experiences and cyber security, stream processing has countless benefits for use cases big and small. By unlocking the power of continuous […]
Announcing ksqlDB 0.24.0
We are excited to announce ksqlDB 0.24! It comes with a slew of improvements and new features. Access to Apache Kafka® record headers will enable a whole host of new […]
Announcing ksqlDB 0.23.1
We’re pleased to announce ksqlDB 0.23.1! This release allows you to now perform pull queries on streams, which makes it much easier to find a given record in a topic. […]
Serverless Stream Processing with Apache Kafka, AWS Lambda, and ksqlDB
It seems like now more than ever developers are surrounded by a sea of terminology—but what does it really all mean? Here, we will take some often heard terms—some considered […]
A Guide to Stream Processing and ksqlDB Fundamentals
Event streaming applications are a powerful way to react to events as they happen and to take advantage of data while it is fresh. However, they can be a challenge […]
How to Efficiently Subscribe to a SQL Query for Changes
Imagine that you have real-time data about what’s happening in the stock market, and you want to support a large number of customized dashboards displaying the data as it comes […]
Announcing ksqlDB 0.22.0
We’re pleased to announce ksqlDB 0.22.0! This release includes source streams and source tables as well as improved pull query (for key-range predicates) and push query performance. All of these […]
How Do You Change a Never-Ending Query?
There’s a philosophical puzzle of the Ship of Theseus where throughout a long voyage planks in a ship are individually replaced as they begin to rot. At the end, there […]
4 Key Design Principles and Guarantees of Streaming Databases
Classic relational database management systems (RDBMS) distribute and organize data in a relatively static storage layer. When queries are requested, they compute on the stored data and then return results […]
The Future of SQL: Databases Meet Stream Processing
SQL has proven to be an invaluable asset for most software engineers building software applications. Yet, the world as we know it has changed dramatically since SQL was created in […]