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meta
rocksdb
C++2013–2026
meta / rocksdb
rocksdb
A library that provides an embeddable, persistent key-value store for fast storage.
52Distinct people
58Mentions
0Explicit recommenders
32.3KGitHub stars
What to know before exploring
What it is
A library that provides an embeddable, persistent key-value store for fast storage.
GitHub
Where it is used
No documented product use was verified in the last source check.
What people are saying
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Also in these discussions
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This week on Hacker News
Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 3:38:16 PM UTC.
Mentions over time
HN mentions by year58 dated mentions
Observed mentions: 2013-11-15 00:22:02 UTC to 2026-06-18 20:03:50 UTC.
* An incomplete calendar period is marked with an outlined bar. Its count is not directly comparable with a full period.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| 2013 | 2013-01-01 00:00:00 UTC | 2014-01-01 00:00:00 UTC | 8 | 1 | 7 |
| 2014 | 2014-01-01 00:00:00 UTC | 2015-01-01 00:00:00 UTC | 2 | 1 | 1 |
| 2015 | 2015-01-01 00:00:00 UTC | 2016-01-01 00:00:00 UTC | 2 | 0 | 2 |
| 2016 | 2016-01-01 00:00:00 UTC | 2017-01-01 00:00:00 UTC | 3 | 1 | 2 |
| 2017 | 2017-01-01 00:00:00 UTC | 2018-01-01 00:00:00 UTC | 10 | 1 | 9 |
| 2018 | 2018-01-01 00:00:00 UTC | 2019-01-01 00:00:00 UTC | 5 | 1 | 4 |
| 2019 | 2019-01-01 00:00:00 UTC | 2020-01-01 00:00:00 UTC | 2 | 1 | 1 |
| 2020 | 2020-01-01 00:00:00 UTC | 2021-01-01 00:00:00 UTC | 4 | 0 | 4 |
| 2021 | 2021-01-01 00:00:00 UTC | 2022-01-01 00:00:00 UTC | 2 | 0 | 2 |
| 2022 | 2022-01-01 00:00:00 UTC | 2023-01-01 00:00:00 UTC | 6 | 2 | 4 |
| 2023 | 2023-01-01 00:00:00 UTC | 2024-01-01 00:00:00 UTC | 6 | 0 | 6 |
| 2024 | 2024-01-01 00:00:00 UTC | 2025-01-01 00:00:00 UTC | 4 | 1 | 3 |
| 2025 | 2025-01-01 00:00:00 UTC | 2026-01-01 00:00:00 UTC | 2 | 0 | 2 |
| 2026 (partial) | 2026-01-01 00:00:00 UTC | 2027-01-01 00:00:00 UTC | 2 | 0 | 2 |
From the project README
An excerpt from the repository, fetched Nov 13, 2026.
Read the project’s introduction
RocksDB: A Persistent Key-Value Store for Flash and RAM Storage
RocksDB is developed and maintained by Facebook Database Engineering Team.
It is built on earlier work on LevelDB by Sanjay Ghemawat (sanjay@google.com)
and Jeff Dean (jeff@google.com)
This code is a library that forms the core building block for a fast
key-value server, especially suited for storing data on flash drives.
It has a Log-Structured-Merge-Database (LSM) design with flexible tradeoffs
between Write-Amplification-Factor (WAF), Read-Amplification-Factor (RAF)
and Space-Amplification-Factor (SAF). It has multi-threaded compactions,
making it especially suitable for storing multiple terabytes of data in a
single database.
Start with example usage here: https://github.com/meta/rocksdb/tree/main/examples
See the github wiki for more explanation.
The public interface is in include/. Callers should not include or
rely on the details of any other header files in this package. Those
internal APIs may be changed without warning.
Questions and discussions are welcome on the RocksDB Developers Public Facebook group and email list on Google Groups.
License
RocksDB is dual-licensed under both the GPLv2 (found in the COPYING file in the root directory) and Apache 2.0 License (found in the LICENSE.Apache file in the root directory). You may select, at your option, one of the above-listed licenses.
Read the full README on GitHubWhat Hacker News says
2 sourcesBlock cache simulator: Add pysim to simulate caches using reinforcement learning
1 points · Open discussion> Badger provides better performance than RocksDB, both in terms of reads and writes.
It's not that simple. It's never that simple.
These are incredibly complex pieces of software designed as generic solutions to a thousand different problems on dozens of platforms. For some combinations of platform+problem these KV stores will do great. But it would be terribly naive to assume it will work in every situation. I can guarantee there are workloads that RocksDB will do better with.
When badger was first released I was pretty skeptical of it... it seemed to be quite buggy, and I tinkered with swapping out our metrics database MDBM-based implementation (yeah that ancient yahoo KV store no one talks about), but it didn't turn out to be a good fit for the use case. It wasn't even in the same ballpark performance-wise. But I hoped that maybe in a
Read the rest
few years it would mature.
This puff piece isn't changing my opinion of it...
The RocksDB folks seem to be a lot more honest about the realities of tuning KV stores: https://github.com/facebook/rocksdb/wiki/RocksDB-Tuning-Guid...
> Unfortunately, configuring RocksDB optimally is not trivial. Even we as RocksDB developers don't fully understand the effect of each configuration change. If you want to fully optimize RocksDB for your workload, we recommend experiments and benchmarking, while keeping an eye on the three amplification factors. Also, please don't hesitate to ask us for help on the RocksDB Developer's Discussion Group.