Apache Hudi is an open table format built around incremental processing — upserts, deletes and change streams over data lake tables. Where the other open table formats optimise for snapshot consistency, Hudi’s distinguishing feature is treating a table as a stream of changes that downstream consumers can subscribe to.
Apache Hudi
Apache Hudi brought record-level upserts and deletes to the data lake, and with them an incremental query model: instead of rescanning a table, a consumer asks what changed since the last commit. That makes it the most stream-shaped of the three open table formats.
- Upserts and deletes - Record-level mutation on object storage, which is what GDPR erasure and CDC ingestion both require.
- Incremental queries - Consumers pull only the changes since a commit, rather than re-reading the table.
- Copy-on-write and merge-on-read - Two storage layouts trading write cost against read cost, chosen per table.
- Built-in table services - Compaction, clustering and cleaning run as managed operations rather than bespoke jobs.
Hudi’s change-stream model is the closest the analytical storage layer gets to the event surface that The State of Data & Analytics APIs found missing from the market’s published contracts: the table knows what changed, and almost nobody describes that to an API consumer.
Industry: Data Engineering
