Apache Paimon vs Graviti
Apache Paimon
paimon.apache.orgGraviti
graviti.comSide by side
| Figure | Apache Paimon | Graviti |
|---|---|---|
| Price from | Free | $200/mo |
| Free plan | Yes | Yes |
| Free trial | — | Yes |
| Open source | — | — |
| Web | — | Yes |
| Windows | Yes | — |
| macOS | Yes | — |
| Linux | Yes | — |
| API | Yes | Yes |
| Self-hosted | Yes | — |
| Plans published | 1 | 3 |
| Spec score · Data Version Control Tools | 9.0 (#2) | 8.0 (#14) |
Plans
In their own words
Apache Paimon
Apache Paimon is a lake format for realtime lakehouse architectures, supporting streaming and batch operations with Flink and Spark. Primary-key tables handle large-scale streaming updates through configurable merge engines, including deduplication, partial updates, aggregation, and first-row updates. Append tables support batch and streaming processing, small-file merging, and compaction with Z-order sorting. Paimon also provides ACID transactions, time travel, schema evolution, and metadata for petabyte-scale datasets and many partitions. Listed integrations include Flink, Spark, Hive, Trino, Presto, StarRocks, and Doris, though supported operations vary by engine and version. Documented CDC sources include MySQL, PostgreSQL, Kafka, MongoDB, and Pulsar. Other capabilities include blob and vector storage, full-text search, and global indexing. PyPaimon provides catalog, table, Arrow, and pandas APIs plus a command-line tool; core reads and writes do not require a JVM or a running Flink or Spark cluster. It is free at free, with users choosing connectors and storage plugins for their environment.
Graviti
Graviti is a data platform for organizing unstructured data used in analytics and AI. It brings raw files, metadata, and semantic data into one place, with customizable filters for querying the latter two. Datasets can be managed through commits and branches, using incremental versioning that avoids duplicating data. Supported material includes images, video, lidar formats such as .pnts, .pcd, .bin, .las, and .ply, as well as time-series and fusion datasets. Annotation options include Classification, Box, Polygon, Polyline, and Cuboid. Users can inspect data and annotation distributions online through lists, histograms, and pie charts without downloading datasets or writing code. Developers can work through a Python SDK, OpenAPI, or command-line interface. Processing workflows can run on commits or manually, and their jobs can use any programming language with Graviti APIs. The platform also offers role-based dataset access, GroundTruth Tools, and marketplace integrations. It is available through web and API. The Starter plan is free; paid plans start at $200/mo, and a 14-day trial is available.