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 www.michael-noll.com
Of Streams and Tables in Kafka and Stream Processing, Part 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.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.
| | 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.
| | rmoff.net
Interesting links - September 2025
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| [AI summary] A blog post from September 2025 highlights various data engineering, AI, and cloud computing topics, including recent developments in tools like DuckDB, Iceberg, and Kafka, along with insights on AI's growing impact.