How will that compare with Flush for example? Anyway, thanks again and keep up the good work. Will try when I find a moment.
Salva On Fri, Jul 31, 2026, 03:27 Zakelly Lan <[email protected]> wrote: > Hi Salva and everyone, > > It is ready. Cobble Flink 0.3.0-1 is now released, with several > performance improvements. Please feel free to try it out if you are > interested. > > I also compared the performance of Cobble and RocksDB [1]. Cobble performs > significantly better in many scenarios and is comparable in others. > Performance, however, is not Cobble’s primary differentiator. Future > development will focus on providing a unified, open, and user-friendly > storage layer for Flink. > > Also cc'ing @Levani who might be interested in this. > > > Best, > Zakelly > > [1] > https://cobble-project.github.io/cobble-flink/latest/state-backend/benchmark.html > > On Tue, Jul 28, 2026 at 11:40 PM Salva Alcántara <[email protected]> > wrote: > >> Looks great! Thanks a lot for sharing, Zakelly. Is it ready to go? I'd >> like to try it out / experiment with it a bit... >> >> Regards, >> >> Salva >> >> On Tue, Jul 21, 2026 at 6:17 PM Zakelly Lan <[email protected]> >> wrote: >> >>> Hi Flink community, >>> >>> I would like to introduce the cobble-flink project, an open-source >>> integration between Apache Flink and the Cobble storage engine[3]. >>> >>> The cobble-flink aims to provide a unified storage for stream >>> processing, covering managed state, sources, and sinks. In particular, it >>> makes Flink state easier to observe, understand, and consume. More details >>> are available in the project repository [1] and documentation [2]. >>> >>> By building on Cobble's remote storage and distributed snapshot >>> capabilities, cobble-flink also enables disaggregated storage, with fast >>> state rescaling when Flink job parallelism changes. >>> >>> Its capabilities are designed to work together around the same persisted >>> data: >>> >>> * Flink jobs write data through the keyed state backend or SQL sink >>> * Other Flink jobs consume it through scans or exact-key lookups >>> * Users/AI agents inspect checkpoints, savepoints, state, timers, and >>> sink snapshots through the web monitor or Java SDK >>> >>> This connects state storage, table storage, downstream consumption, and >>> inspection in one workflow. Persisted state can be displayed as named, >>> typed fields, consumed through Flink SQL, and reused in lookup joins or new >>> pipelines. >>> >>> The cobble-flink supports Flink 1.17 and later. It is licensed under >>> Apache License 2.0 and is an independent project. >>> >>> The project is currently under rapid development and is not yet >>> recommended as a mature production solution. Ideas, feedback, and >>> contributions are very welcome. >>> >>> >>> Best regards, >>> Zakelly >>> >>> >>> [1] https://github.com/cobble-project/cobble-flink >>> [2] https://cobble-project.github.io/cobble-flink/latest >>> [3] https://github.com/cobble-project/cobble >>> >>
