GitHub user MisterRaindrop added a comment to the discussion: [DISCUSSION] Making Apache Cloudberry an Agent-Native Analytical Database
## Lance adoption across Apache projects Another useful signal is that Lance is no longer isolated from the broader Apache data ecosystem. Several ASF projects already include released Lance integrations at different layers: - [Apache Hudi 1.2](https://hudi.apache.org/releases/release-1.2/) supports Lance as a base-file format for vector and blob-oriented tables. - [Apache Paimon 2.0](https://paimon.apache.org/docs/2.0/concepts/spec/fileformat/#lance) includes Lance file-format readers and writers. - [Apache Fluss](https://fluss.apache.org/docs/streaming-lakehouse/integrate-data-lakes/lance/) provides a Lance lake connector that continuously tiers streaming data into standard Lance tables. - [Apache Gravitino](https://gravitino.apache.org/docs/1.3.0/lance-rest-service/) provides a Lance REST service for namespace, table, and metadata management. - [Apache SeaTunnel](https://seatunnel.apache.org/docs/connectors/sink/Lance/) provides a Lance sink for batch and streaming ingestion. There are also ecosystem-level integrations with Apache Spark, Apache Flink, and Apache DataFusion maintained by the Lance community, while [Apache Polaris](https://polaris.apache.org/blog/2026/01/06/apache-polaris-and-lance-bringing-ai-native-storage-to-the-open-multimodal-lakehouse/) can manage Lance tables through its Generic Table API and a Lance Namespace adapter. These integrations cover several complementary layers: ```text SeaTunnel / Fluss → ingestion and streaming tiering Hudi / Paimon → table and file-format integration Gravitino / Polaris → catalog, namespace, and governance Spark / Flink / DataFusion → processing and query-engine integration ``` This does not mean that all of these projects use Lance as their default storage format, but it does show growing interoperability and real implementation work across ASF projects. For Cloudberry, the opportunity would be to add a PostgreSQL-compatible MPP analytical path over Lance: distributed scans, joins with native or Iceberg data, Vector Top-K pushdown, and higher-level analytical/RAG capabilities exposed through MCP. GitHub link: https://github.com/apache/cloudberry/discussions/1967#discussioncomment-18323892 ---- This is an automatically sent email for [email protected]. To unsubscribe, please send an email to: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
