Apr 8 · 17 min read · A Brief History of the Lakehouse To understand where lakehouse architecture stands in 2026, it helps to trace how it got here. The data lake era (2010s) began when S3 made object storage cheap enough to store everything. Teams dropped raw files (JSON...
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Apr 8 · 15 min read · Why Apache Iceberg Won Three open table formats competed for the lakehouse standard over the past several years: Apache Iceberg, Delta Lake (Databricks), and Apache Hudi (Uber). By 2026, Iceberg emerged as the format that every major data platform su...
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Apr 3 · 7 min read · RisingWave enables real-time analytics on Apache Iceberg tables by continuously ingesting data from Kafka and databases into Iceberg via streaming sinks, and — in v2.8+ — directly querying Iceberg tables as sources. This means your dashboards and app...
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Apr 3 · 7 min read · Apache Iceberg, Delta Lake, and Apache Hudi are all open table formats that bring ACID transactions and reliable analytics to data lakes. Iceberg offers the broadest multi-engine support and most flexible metadata design. Delta Lake has the deepest S...
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Apr 3 · 6 min read · A real-time data lakehouse with RisingWave and Apache Iceberg on S3 gives you sub-minute data freshness, full SQL analytics, and object storage costs — without a proprietary data warehouse. RisingWave streams data continuously into Iceberg tables on ...
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Apr 3 · 6 min read · Apache Iceberg is an open table format for large analytic datasets. It brings ACID transactions, schema evolution, time travel, and partition evolution to data lakes stored on object storage like S3, GCS, or ADLS — enabling reliable, high-performance...
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Apr 3 · 5 min read · The Iceberg REST Catalog specification provides a vendor-neutral HTTP API for managing Iceberg table metadata. RisingWave integrates with any compliant REST catalog — including the open-source Iceberg REST server, Project Nessie, Tabular, AWS Glue (v...
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Apr 3 · 6 min read · Apache Iceberg v3 introduces native variant and geometry types, row-level encryption, default column values, and multi-argument transforms — while remaining backward compatible with v2 readers for tables that don't use new features. For RisingWave us...
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Apr 3 · 5 min read · A real-time data lakehouse on AWS combines Apache Iceberg's open table format with RisingWave's stream processing to deliver sub-second data freshness directly into S3-backed tables. RisingWave ingests events from Kafka or CDC sources, applies contin...
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Apr 3 · 5 min read · A fintech data lakehouse with RisingWave and Apache Iceberg means using RisingWave to process streaming financial events in real time, then sinking the results as Iceberg tables on object storage—giving you sub-second operational queries on RisingWav...
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