Lakehouse platforms & table formats · Apache Software Foundation (originated by Uber)
Apache Hudi
Open-source table format optimized for high-volume upserts, deletes, and incremental data-lake pipelines.
Apache Hudi is an open-source table format and set of libraries, originally built at Uber, focused on making frequent, record-level upserts and deletes fast on a data lake, a pattern common in change-data-capture (CDC) pipelines and workloads with strict data-deletion requirements. It provides two table storage options: Copy-on-Write, which rewrites files immediately for fast reads, and Merge-on-Read, which logs changes separately and merges them at read or compaction time for faster writes. Hudi ships built-in indexing to accelerate upsert lookups, incremental queries so downstream jobs can process only changed records, and integrations with Spark, Flink, Presto, and Trino. It is a library that runs inside existing compute engines rather than a managed service, though the commercial venture Onehouse offers a managed lakehouse built on Hudi.
At a glance
| Vendor | Apache Software Foundation (originated by Uber) |
|---|---|
| Pricing model | Open source + paid options |
| Free tier | Yes |
| Deployment | Self-hosted |
| Open source | Yes (Apache-2.0) |
| Best for | Pipelines with heavy upsert/delete volume, such as CDC ingestion or GDPR-driven record deletion. |
Pricing
Free, open-source table format; no vendor pricing, though managed services built on Hudi (such as Onehouse) are sold separately.
Pricing has not been verified yet — see the vendor's site.
Features
- Record-level upserts and deletes optimized for CDC pipelines
- Copy-on-Write and Merge-on-Read storage layouts
- Built-in indexing for fast upsert/delete lookups
- Incremental queries returning only changed records
- Automatic file sizing, clustering, and compaction services
- Multi-engine support (Spark, Flink, Presto, Trino, Hive)
- Time travel and savepoints for rollback
Integrations
Profile last reviewed September 21, 2026