It depends on workloads, in most cases, there is at least 3x perf gain. One of our customer get 20x perf gain(point search).

Another significant improvement is `select count(*) from SomeTable` in MyTopling, I optimized such query by 30x+ faster than MyRocks, 10x+ faster than InnoDB, while the multi-thread scaling is near linear -- better than InnoDB.

We keep the core component as private repo, which builds the ToplingZipTable files -- the SST with the searchable compression algo for speed. -- Although even without this component, ToplingDB is still outperforms RocksDB.

Sure, this is one of the reason we develop the framework of json/yaml conf and the embedded http server, with this framework, we discover several RocksDB bugs by this framework(we have contributed 100+ PRs and 60+ issues for RocksDB).

With embedded http server, all DB configurations and status are visually displayed, for example: the compaction progress, the SST file list with the compacting files are highlighted -- with different colors for different compaction jobs, different icons for different compaction types(https://github.com/topling/sideplugin-wiki-en/wiki/Compactio...)

Like RocksDB from which this appears to be forked, the primary usage is as a storage engine for other applications/databases. Compared to rocksdb, it seems like ToplingDB has added more facilities to better support distributed use-cases.

Some databases that utilize RocksDB for their storage engine: https://kvrocks.apache.org/ - Redis/ValKey compatible distributed database with disk persistence via RockDB. https://github.com/pingcap/tidb - MySQL compatible distributed database. Mentioned elsewhere in this thread. https://github.com/tikv/tikv - Distributed, transactional, key value store. Originally by the same company as TiDB.

In theory you could use it as an in-process KV store similar to how SQLite provides an in process sql database, but the api is far from ergonomic for that use case.

Thank you!

Yes, we have S3 solution with ToplingDB for enterprise users.

It's quite active. They just aren't using GitHub pull requests in their workflow, which is what GitHub Pulse measures. https://github.com/topling/toplingdb/commits/memtable_as_log...

Thank you, we have fixed READM, now it's very easy to start with ToplingDB by the tutorial in README.

It’s RocksDB but faster because data can be searched while still compressed allowing you to load more records in less cache/ram leading to up to 10x performance of RocksDB. It adds an embedded http control plane as well as supporting other extensions like MyRocks (MySQL) and Todis (redis compatibility).

Or at least thats what I got from it correct me if I am wrong rockeet.

From what I gather it has an embedded http control plane, yaml/json config for plugins, prometheus integration, and distributed compaction workers on separate, potentially serverless, hosts.

It has an embedded http server?