Lakehouse platforms & table formats · Apache Software Foundation
Apache Paimon
Open-source lake table format built for unified streaming and batch updates, originating from the Apache Flink community.
Apache Paimon is an open-source table format built primarily by the Apache Flink community to close a gap the older lake formats had: fast, high-throughput streaming writes combined with efficient batch reads on the same table. It uses an LSM-tree-based storage layout, similar to key-value stores, so continuous streaming upserts land quickly and are later compacted for efficient analytical scans, rather than relying purely on file-rewrite or log-merge patterns. Paimon integrates tightly with Flink for real-time ingestion and also supports Spark, Trino, and Hive for batch analytics, and it can act as an interchange format with Iceberg and Hive metastores. It is a library and specification, not a managed product, so teams adopt it by configuring Flink or Spark jobs to read and write Paimon tables on existing object storage.
At a glance
| Vendor | Apache Software Foundation |
|---|---|
| Pricing model | Open source + paid options |
| Free tier | Yes |
| Deployment | Self-hosted |
| Open source | Yes (Apache-2.0) |
| Best for | Streaming-heavy pipelines needing fast continuous writes and efficient batch analytics on one table. |
Pricing
Free, open-source table format with no vendor pricing; costs are limited to the compute and storage it runs on.
Pricing has not been verified yet — see the vendor's site.
Features
- LSM-tree storage layout for fast streaming upserts
- Unified streaming and batch reads on the same table
- Deep native integration with Apache Flink
- Background compaction to keep batch queries efficient
- Schema evolution and time travel
- Changelog production for downstream streaming consumers
- Interoperability bridges toward Iceberg and Hive metastore
Integrations
Profile last reviewed September 21, 2026