Skip to content

Comment on EloqKV: Achieving Predictable P99.99 Latency on NVMe with Redis API

Comments

With DRAM price this high, this is certainly a welcome feature. But how do you control write latency? B+ Tree is pretty bad at updates and LMDB, another BTree based storage is lightning fast on reads but quite bad on writes compared with RocksDB.

The disk storage EloqKV uses (EloqStore [1]) is optimized for batch updates because the upper Data Substrate layer manages buffering and the Write-Ahead Log (WAL), absorbing writes and guaranteeing durability. When durability is not required, the WAL can be optionally disabled.

[1] github.com/eloqdata/eloqstore

Disclaimer: I am the CEO of EloqData

we leverage batch write optimization which uses Copy-on-write B-tree variant enables high-throughput batch writes without blocking concurrent reads. MVCC-based design eliminates lock contention and provides predictable write amplification.

AboutSource Built by g1lg1l

Hackerly is an independent reader for Hacker News, built on the public HN API. Not affiliated with Y Combinator.