775 tutorials · free to read
A working handbook for data and software engineering.
Hands-on tutorials by Alex Merced on Apache Iceberg, the data lakehouse, pipelines, agentic AI, and the languages and tools that hold it all together.
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Latest tutorials
Page 39 of 130- 01Iceberg v4 Performance: Root Manifests and CallsApache Iceberg v4 discussion should focus on planning cost, metadata layout, and object storage round trips, not vague claims about faster tables.LakehouseJun 22, 2026
- 02What Is LTAP in the Lakehouse?Lakehouse transactional analytical processing is useful only when teams define freshness, isolation, and workload boundaries clearly.LakehouseJun 22, 2026
- 03The Model Is Not the MoatEnterprise AI advantage increasingly comes from governed context, semantic models, and operational data contracts, not only from model choice.LakehouseJun 22, 2026
- 04PyIceberg at Scale Without Apache SparkPython-first Iceberg work is useful when it stays honest about what Python should and should not do.LakehouseJun 22, 2026
- 05The Real-Time Lakehouse with Streaming and IcebergThe real-time lakehouse is not one engine. It is a contract between streams, table commits, query paths, and freshness expectations.LakehouseJun 22, 2026
- 06REST Catalog V2 LoadTable and Client CapabilityREST Catalog V2 LoadTable work matters because clients and catalogs need explicit contracts, not optimistic assumptions.LakehouseJun 22, 2026