Database Streaming with Apache Kafka

To get a streaming database production ready, there are steps required to get it right. The Stream Processing team led by Michael Drogalis (Principal Product Manager, Confluent), also the folks who helped build ksqlDB—a streaming database purpose-built for stream processing applications, available in Confluent Cloud, has released a series of technical papers on the Confluent blog to tell you all about streaming databases.

The series includes blog posts by:
► Michael Drogalis (Principal Product Manager, Confluent), who explains the foundations in streaming database design and adopting SQL for streaming and data in motion:

► Michael Noll (Principal Technologist, Office of the CTO, Confluent) and Matthias Sax (​​Staff Software Engineer I, Product Infrastructure, Confluent), who describe how SQL has shifted from a language for data at rest into a language that is capable of handling data in motion:

► Guozhang Wang (Principal Engineer II, Confluent), who explains the design foundations of a streaming database and identifies the differences between a streaming database and a relational database:

► Almog Gavra (Senior Software Engineer, Product Infrastructure, Confluent), who has experience managing ksqlDB’s query layer and walks through how streaming databases cope with changes to query workloads without incurring downtime:

Through this series of blog posts, we hope to share findings that support your Apache Kafka® journey.

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