Quickstart to Apache Kafka Stream Processing with KsqlDB

Quickstart to Apache Kafka Stream Processing with KsqlDB

Kafka is the de-facto standard for collecting and storing event data. ksqlDB is a purpose-built database for stream processing. Basic knowledge of Apache Kafka will help the reader, but isn’t required. Quickstart to Apache Kafka Stream Processing with ksqlDB.

Kafka is the de-facto standard for collecting and storing event data — but are you comfortable using that data in your applications in real-time? It’s trickier than it seems — you need to integrate, secure and scale different systems for event storage, processing and querying. This is why we created  ksqlDB, a database purpose-built for stream processing applications.

What Is Stream Processing?

Kafka is great for working with events through its durable, append-only log. Taking action on those streams of events in real-time, however, can be a challenge. This is where a stream processor such as ksqlDB comes in. KsqlDB provides a processing model for working with groups of events as if they were in-memory collections and makes them accessible through SQL.

Stream processing deals with data *events *as they come in and pushes them into pipes known as *topics *as they go out. The data is immutable, so applications can read from a topic, compute new information, and then push the result into another topic as needed.

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