Streamhouse Architecture with Flink and Paimon
summary
Claims a workable streaming lakehouse built with Flink + Apache Paimon + Flink CDC, not just hype: Paimon is a table format tuned for streaming with upserts and time travel and S3-backed snapshots, Flink runs continuous SQL/dataflow and uses a Paimon connector for reads/writes, and Flink CDC streams RDBMS changes with a snapshot→incremental transition. The demo builds a continuous airline join and aggregation that runs in production-style mode, preserves exactly-once semantics, and aims for lower cost than always-online Kafka systems.
AI-written summary · about
chapters (8)
- 0:00Streamhouse architecture intro
- 1:45Flink overview and capabilities
- 7:28Paimon table format
- 16:20Flink CDC for databases
- 20:56Flink Paimon CDC integration
- 27:41Streamhouse use case with Flink SQL
- 33:18Key takeaways
- 33:41Q&A
related talks
40mThe Seven Deadly Sins of Streaming
43mHail Hydrate! From Stream to Lake Using Open Source
01h 01mApache Fluss: A Streaming Storage for Real-Time Lakehouse
51mStream Processing Smackdown: Kafka Streams vs. Apache Flink
42mStream Processing with Apache Flink
23mBetter, Faster, Stronger Streaming: Your First Dive into Flink SQL
31mFrom Warehouse to Lakehouse: Data at Rest
39mFaster Analytics for Fast Data with Apache Pinot and Flink SQL
