Confluent Blog

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

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

“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

Apache Kafka® is a distributed real-time processing platform that allows for the ingestion of huge volumes of data. ksqlDB is part of the Kafka ecosystem and offers a SQL-like language

It’s important to be able to limit memory consumption of a running service. Use too much, and your application will crash and need to restart. If this happens too often,

All around the world, companies are asking the same question: What is happening right now? We are inundated with pieces of data that have a fragment of the answer. But

Stream processing applications, including streaming ETL pipelines, materialized caches, and event-driven microservices, are made easy with ksqlDB. Until recently, your options for interacting with ksqlDB were limited to its command-line

The ksqlDB team is pleased to announce ksqlDB 0.12.0. This release continues to improve upon the usability of ksqlDB and aims to reduce administration time. Highlights include query upgrades, which

ksqlDB, the event streaming database, is becoming one of the most popular ways to work with Apache Kafka®. Every day, we answer many questions about the project, but here’s a

When operating cloud infrastructure, “time is money” is more than a cliché—it is interpreted literally as every processing second stacks up on the monthly bill. ksqlDB strives to reduce these