yottaStore VS kvrocks

I'm building a database, and I'm working on the storage format. For each record I have a logical clock which increases by 1 every time there's a write operation on the record, and I would like to be able to compare the clocks of two writes to understand which happened first.

If you're curious to know more, the tree is used for rendezvous based routing, as used by my datastore. I'm doing machine learning on a 200 TB dataset, using around 200 machines.

I copied this approach from several papers, with some improvements, for my datastore.

I have a server with hundreds of routes, representing all the possible operations I can do on a datastore. How can I organize my code better?

Yes I'm building a database where storage and compute are decoupled. I use io_uring to do pseudo-RDMA, and I'm looking to add ePBF to make it even more effective.

I'm currently building an implementation of the dynamo paper, yottastore. Imagine it as a huge, distributed, hash map.

I'm building an implementation of the dynamo paper, yottastore. Given a key, I need to find which NVMe block stores the data. To do that I hash the key to find the shard where I have an in memory array in which at position [hash] I can find a struct with:

I have to be honest, I'm very skeptical about your results and your code. I'm building a database, yottastore, both in javascript, golang and rust so I think I can share my opinion:

I switched from SSDB to Kvrocks recently, because SSDB is abandoned and the author missing for 3 years now. I used to recommend SSDB, but now there's better alternatives available:

https://github.com/apache/kvrocks

https://github.com/sabledb-io/sabledb

Another under the radar Apache project I've found myself using is Apache KvRocks

https://github.com/apache/kvrocks

It's a Redis compatible database on top of RocksDB, so unlike Redis it uses the disk instead of RAM, but you can control how much data is cached in RAM, obviously Kvrocks will be slower than Redis for uncached data.

Useful in situations where you want a KV data store that isn't limited by your memory specs but is compatible with everything that speaks Redis.

There’s Kvrocks. It uses the Redis protocol and it’s built on RocksDB https://github.com/apache/kvrocks

Apache Kvrocks is a distributed key-value NoSQL database that uses RocksDB as a storage engine and is compatible with Redis protocol.

We use Kvrocks[0] at work. It is Redis on disk, powered by "RocksDB" (hence the name) and compatible with most of the Redis clients since it respects the Redis protocol. It was incubated by Apache earlier this year.

It works great and the development is really active.

[0]: https://kvrocks.apache.org