Data Lakehouse

Quick answer

There is no universal lakehouse winner. Choose by engine ecosystem and table-format commitments. Apache Iceberg fits neutral open table format needs, Delta Lake fits Spark and Databricks stacks, and Apache Hudi fits upserts and incremental ingestion.

Top picks in Data Lakehouse

Apache Iceberg
Open table format
Fits teams that want an open table format across multiple query engines with schema evolution and partition evolution.
Delta Lake
Spark lakehouse
Fits teams already centered on Spark or Databricks that want ACID tables, time travel, and batch or streaming writes.
Apache Hudi
Upsert pipelines
Fits pipelines that need record-level upserts, incremental processing, and CDC-style lakehouse ingestion.

Apache Hudi

Lakehouse Platform for Incremental Processing

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Apache Hudi is an open data lakehouse platform that enables efficient record-level upserts, incremental processing, and ACID transactions on data lakes.

Apache Iceberg

Open Table Format for Huge Analytic Datasets

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Apache Iceberg is a high-performance open table format enabling multi-engine analytics with schema evolution, time travel, and hidden partitioning.

Delta Lake

Open-Source Lakehouse Storage Framework

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Delta Lake is an open-source storage framework that brings ACID transactions, schema evolution, and time travel to data lakes at petabyte scale.

A curated collection of the best data lakehouse platforms combining data lake storage with warehouse query capabilities for scraped data.

Quick answer

Top picks in Data Lakehouse