Apache Paimon
Apache Paimon: A flexible open-source choice for streaming tables, CDC pipelines, and lakehouse architectures. Ranked #5 of 36 in Data Version Control Tools by our editors (8.7/10); pricing: Free plan; best for streaming table and CDC pipelines.
At a glance
- Editor score8.7 / 10
- PricingFree plan
- Best forStreaming table and CDC pipelines
- Free planYes
- Paid fromFree
- Data scopeTables
- Facts checked22 Sep 2026
Where it wins
- Snapshots, branches, tags, time travel, and rollback support
- Streaming reads and writes with CDC ingestion pipelines
- Integrates with Flink, Spark, Hive, Trino, and more
Where it doesn't
- Self-hosted deployment requires you to manage the environment
- Storage is bring-your-own rather than bundled
- Java and Python are the listed API languages
Our verdict on Apache Paimon
Apache Paimon is an open-source lake format from the Apache Software Foundation for teams building realtime lakehouse architectures around tables. It supports append and primary-key tables, organizing data with schemas, snapshots, manifests, and data files. Its audience includes teams running batch and streaming engines that need table versioning, streaming updates, CDC ingestion, and schema evolution. Java and Python APIs support application-level access, while the self-hosted deployment model suits organizations that manage their own infrastructure and storage systems.
Versioning is a central strength. Paimon provides table snapshots and time travel, along with dataset branches, tags, and rollback to snapshots or tags. Compaction and snapshot expiration address table maintenance, while incremental reads support ongoing data processing. The format also covers streaming reads and writes, schema evolution, append and primary-key table models, and CDC ingestion pipelines. For workloads extending beyond conventional tables, its listed storage capabilities include vector, full-text, and blob storage.
Ecosystem fit is broad for an open-source table format. Integrations include Apache Flink, Apache Spark, Apache Hive, Trino, Presto, StarRocks, Doris, and Amoro, giving teams multiple engine and query options. Paimon can use local or external storage systems, but the published deployment model is self-hosted and the storage backend is bring-your-own. Choose it when open table versioning, streaming, CDC, and engine flexibility matter more than a managed service experience. Teams seeking bundled infrastructure or a hosted operating model should consider alternatives built around managed deployment.
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Apache Paimon pricing
Apache Paimon fact sheet
| Free plan | Yes |
|---|---|
| Paid from | Free |
| Data scope | Tables |
| Dataset branching | Yes |
| Point-in-time rollback | Yes |
| Snapshot granularity | Table |
| Storage backend | Bring_your_own |
| Deployment model | Self_hosted |
| Deployment | Self-hosted |
| Support | Community, Docs |
| Built for | Mid-market, Enterprise (editorial estimate) |
| Integrations | 8 integrations: Apache Flink, Apache Spark, Apache Hive, Trino, Presto, StarRocks … See all → |
| Pricing | Free plan |
| Website | paimon.apache.org |
| Facts checked | 22 Sep 2026 |
Apache Paimon integrations
Apache Paimon lists 8 integrations on its own site.
- Apache Flink
- Apache Spark
- Apache Hive
- Trino
- Presto
- StarRocks
- Doris
- Amoro
See all Apache Paimon integrations →
Alternatives to Apache Paimon
- lakeFSOpen-source, Git-like version control for governed data on object storage.9.4
- DoltGit-style table versioning with MySQL compatibility and open-source deployment.9.2
- DataLadA free, technical toolkit for versioning, reproducing, and synchronizing large file datasets.9.0
See all Apache Paimon alternatives →
Apache Paimon vs the competition
- Apache Paimon vs lakeFS
- Apache Paimon vs Dolt
- Apache Paimon vs DataLad
- Apache Paimon vs git-annex
- Apache Paimon vs Oxen
- Apache Paimon vs Project Nessie
Compare Apache Paimon with any tool side by side →
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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