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 www.michael-noll.com
Of Streams and Tables in Kafka and Stream Processing, Part 1
| | www.morling.dev
Backfilling Postgres TOAST Columns in Debezium Data Change Events - Gunnar Morling
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| | Postgres logical replication, while powerful for capturing real-time data changes, presents challenges with TOAST columns, whose values can be absent from data change events in specific situations. This post discusses how Debezium addresses this through its built-in reselect post processor, then explores more robust solutions leveraging Apache Flink's capabilities for stateful stream processing, including Flink SQL and the brand-new process table functions (PTFs) in Flink 2.1.
| | blog.florimondmanca.com
Breaking News: Everything Is An Event! (Streams, Kafka And You) - Florimond Manca
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| | It's about time you met streaming data! I'm sure you two and Apache Kafka will do great things together.
| | www.madewithtea.com
Made with Tea: Jendrik Poloczek
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| | This article is about aggregates in stateful stream processing in general. I write about the differences between Apache Spark and Apache Kafka Streams along concrete code examples. Further, I list the requirements which we might like to see covered by a stream processing framework.
| | www.kai-waehner.de
Apache Kafka vs. Integration Middleware (MQ, ETL, ESB) - A Comparison
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| Blog about architectures, best practices and use cases for data streaming, analytics, hybrid cloud infrastructure, internet of things, crypto, and more