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rocksdb
C++2013–2026
meta / rocksdb

rocksdb

A library that provides an embeddable, persistent key-value store for fast storage.

Data & DatabasesLibraries & SDKs
Explore on GitHubRead Hacker News discussions
52Distinct people
58Mentions
0Explicit recommenders
32.3KGitHub stars
REPOSITORY AT A GLANCE

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

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 1:49:46 PM UTC.

[dead] direct repository link

Read the discussion on HN. A full-thread summary is not available yet.

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.

02468102013-01-01 00:00:00 UTC to 2014-01-01 00:00:00 UTC (exclusive): 8 mentions; 1 submissions, 7 comments20132014-01-01 00:00:00 UTC to 2015-01-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 comments2015-01-01 00:00:00 UTC to 2016-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 3 mentions; 1 submissions, 2 comments2017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 10 mentions; 1 submissions, 9 comments2018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 5 mentions; 1 submissions, 4 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 comments20192020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 4 mentions; 0 submissions, 4 comments2021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 6 mentions; 2 submissions, 4 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 6 mentions; 0 submissions, 6 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 4 mentions; 1 submissions, 3 comments2025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2026-01-01 00:00:00 UTC to 2027-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments. Incomplete calendar period.2026*

* 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
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20132013-01-01 00:00:00 UTC2014-01-01 00:00:00 UTC817
20142014-01-01 00:00:00 UTC2015-01-01 00:00:00 UTC211
20152015-01-01 00:00:00 UTC2016-01-01 00:00:00 UTC202
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC312
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC1019
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC514
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC211
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC404
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC202
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC624
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC606
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC413
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC202
2026 (partial)2026-01-01 00:00:00 UTC2027-01-01 00:00:00 UTC202

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 GitHub

What Hacker News says

58 sources
ozgrakkurt·Feb 22, 2026
You can actually make those two bits more independent afaik. https://github.com/apache/parquet-format/blob/master/BloomFi... https://github.com/facebook/rocksdb/blob/main/util/bloom_imp... First one is useful for grasping the idea second one is more comprehensive. Both try to make multiple bit loads but try to make them as independent as possible as far a I can understand. Also hash function has huge effect on bloom filter performance. I was getting 2x perf when using xxhash3 instead of wyhash even though wyhash is a faster hash function afaik.
In Two Bits Are Better Than One: making bloom filters 2x more accurate
gritzko·Jun 25, 2024
Excellent. This approach to CRDTs existed even before the term itself was invented. In the 2010 article[2] on Causal Trees[1], your humble servant calls these per-peer op logs "yarns". In the 2011, observing the proliferation of proposals, Shapiro&friends propose[3] the term "CRDT". That is essentially a partially-ordered approach to oplogs. Oplogs (binlogs, WALs) underlie the entire universe of databases. The problems are exactly the same as the problems "normal" database developers faced in the far past: how much history do you want to keep? How to synchronize the log and the state reliably? What is the format of the log? How to store/transfer the log reliably? The last question seems trivial, but it is not. If you read some databases' source code, you may find a lot of paranoid things[4], obviously inspired by humiliating real-life inc
Read the rest
idents. The other questions are not trivial by any means. So, yes, this is the way[5]. [1]: Alexei "archagon" Baboulevitch excellent popular summary of Causal Trees, 2018 http://archagon.net/blog/2018/03/24/data-laced-with-history/ [2]: The 2010 paper https://www.researchgate.net/publication/221367739_Deep_hype... [3]: The CRDT paper https://pages.lip6.fr/Marc.Shapiro/papers/RR-7687.pdf [4]: e.g. https://github.com/facebook/rocksdb/blob/main/db/log_reader.... [5]: the simultaneous post by Nikita Prokopov https://tonsky.me/blog/crdt-filesync/
In Resilient Sync for Local First
magicalhippo·Jul 4, 2023
Internally, ZFS is kinda like an object store[1], and there was a project trying to expose the ZFS internals through an object store API rather than through a filesystem API. Sadly I can't seem to find the presentation or recall the name of the project. On the other hand, looking at for example RocksDB[2]: File system operations are not atomic, and are susceptible to inconsistencies in the event of system failure. Even with journaling turned on, file systems do not guarantee consistency on unclean restart. POSIX file system does not support atomic batching of operations either. Hence, it is not possible to rely on metadata embedded in RocksDB datastore files to reconstruct the last consistent state of the RocksDB on restart. RocksDB has a built-in mechanism to overcome these limitations of POSIX file system [...] ZFS does provide atomic o
Read the rest
perations internally[1], so if exposed it seems something like RocksDB could take advantage of that and forego all the complexity mentioned above. How much that would help I don't know though, but seems potentially interesting at first glance. [1]: https://youtu.be/MsY-BafQgj4?t=442 [2]: https://github.com/facebook/rocksdb/wiki/MANIFEST
In ZFS 2.2.0 (RC): Block Cloning merged
Rochus·Jun 11, 2023
The most obvious alternative is https://sourceforge.net/projects/fis-gtm/, but there are a few others, depending on the size of the application at hand. https://yottadb.com/ is another big one which started on GT.M a few years ago, or http://minimdb.com/. See also https://www.mumps.dev/implementations.cfm. If you don't depend on the MUMPS/ANSI-M language or don't have to be backwards compatible, a lot more alternatives with similar features are available, e.g. https://github.com/facebook/rocksdb run behind e.g. Node.js.
In A Case of the MUMPS (2007)
l05k·Apr 20, 2023
I would recommend a related paper, "Building an Efficient Key-Value Store in a Flexible Address Space", which focused on the interaction problem between extent-based filesystem and key-value store. However, in scenarios that really care about performance, memory-mapped files seem to be able to bypass the I/O stack and optimize performance. RocksDB also has corresponding optimizations: https://github.com/facebook/rocksdb/wiki/PlainTable-Format
In How RocksDB Works
zX41ZdbW·Feb 2, 2023
We use seven different types of fuzzing in ClickHouse, including OSS-Fuzz: https://clickhouse.com/blog/fuzzing-click-house And I can confirm - writing software in C++ without fuzzing is insane. We are finding and fixing memory-safety bugs in every third-party library that we use. For example, there are bugs in RocksDB: https://github.com/facebook/rocksdb/issues?q=is%3Aissue+clic... Here are some bugs in JeMalloc: https://github.com/jemalloc/jemalloc/issues/2222 Strangely, these bugs were found by the CI of ClickHouse, and not by any of the hundreds of other products using these libraries.
In Google's OSS-Fuzz expands fuzz-reward program

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