sky-benches
RocksDB
sky-benches | RocksDB | |
---|---|---|
7 | 43 | |
15 | 27,424 | |
- | 0.7% | |
1.8 | 9.8 | |
about 2 years ago | about 5 hours ago | |
Shell | C++ | |
MIT License | GNU General Public License v3.0 only |
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Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
sky-benches
- Skytable NoSQL Database: Even with BlueQL, Skytable Outperforms Redis and KeyDB
- So, you call yourself the fastest key/value store? It's 5X, 10x and 25X faster
- Ask HN: What are the best key-value self-hosted storage engines?
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Skytable: A NoSQL database project in Rust about 10X faster than Redis
UPDATE: I have published some initial benchmarks against KeyDB here: https://github.com/ohsayan/sky-benches. Oddly enough, the bump in the number of queries in KeyDB is similar to that of Skytable. If anyone has suggestions or find something to be anomalous, please open an issue!
RocksDB
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How to choose the right type of database
RocksDB: A high-performance embedded database optimized for multi-core CPUs and fast storage like SSDs. Its use of a log-structured merge-tree (LSM tree) makes it suitable for applications requiring high throughput and efficient storage, such as streaming data processing.
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Fast persistent recoverable log and key-value store
[RocksDB](https://rocksdb.org/) isn’t a distributed storage system, fwiw. It’s an embedded KV engine similar to LevelDB, LMDB, or really sqlite (though that’s full SQL, not just KV)
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The Hallucinated Rows Incident
To output the top 3 rocks, our engine has to first store all the rocks in some sorted way. To do this, we of course picked RocksDB, an embedded lexicographically sorted key-value store, which acts as the sorting operation's persistent state. In our RocksDB state, the diffs are keyed by the value of weight, and since RocksDB is sorted, our stored diffs are automatically sorted by their weight.
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In-memory vs. disk-based databases: Why do you need a larger than memory architecture?
The in-memory version of Memgraph uses Delta storage to support multi-version concurrency control (MVCC). However, for larger-than-memory storage, we decided to use the Optimistic Concurrency Control Protocol (OCC) since we assumed conflicts would rarely happen, and we could make use of RocksDB’s transactions without dealing with the custom layer of complexity like in the case of Delta storage.
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Local file non relational database with filter by value
I was looking at https://github.com/facebook/rocksdb/ but it seems to not allow queries by value, as my last requirmenet.
- Rocksdb over network
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How RocksDB Works
Tuning RocksDB well is a very very hard challenge, and one that I am happy to not do day to day anymore. RocksDB is very powerful but it comes with other very sharp edges. Compaction is one of those, and all answers are likely workload dependent.
If you are worried about write amplification then leveled compactions are sub-optimal. I would try the universal compaction.
- https://github.com/facebook/rocksdb/wiki/Universal-Compactio...
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What are the advantages of using Rust to develop KV databases?
It's fairly challenging to write a KV database, and takes several years of development to get the balance right between performance and reliability and avoiding data loss. Maybe read through the documentation for RocksDB https://github.com/facebook/rocksdb/wiki/RocksDB-Overview and watch the video on why it was developed and that may give you an impression of what is involved.
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We’re the Meilisearch team! To celebrate v1.0 of our open-source search engine, Ask us Anything!
LMDB is much more sain in the sense that it supports real ACID transactions instead of savepoints for RocksDB. The latter is heavy and consumes a lot more memory for a lot less read throughput. However, RocksDB has a much better parallel and concurrent write story, where you can merge entries with merge functions and therefore write from multiple CPUs.
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Google's OSS-Fuzz expands fuzz-reward program to $30000
https://github.com/facebook/rocksdb/issues?q=is%3Aissue+clic...
Here are some bugs in JeMalloc:
What are some alternatives?
skytable - Skytable is a modern scalable NoSQL database with BlueQL, designed for performance, scalability and flexibility. Skytable gives you spaces, models, data types, complex collections and more to build powerful experiences
LevelDB - LevelDB is a fast key-value storage library written at Google that provides an ordered mapping from string keys to string values.
KeyDB - A Multithreaded Fork of Redis
LMDB - Read-only mirror of official repo on openldap.org. Issues and pull requests here are ignored. Use OpenLDAP ITS for issues.
dragonfly - A modern replacement for Redis and Memcached
SQLite - Unofficial git mirror of SQLite sources (see link for build instructions)
Memcached - memcached development tree
sled - the champagne of beta embedded databases
MapDB - MapDB provides concurrent Maps, Sets and Queues backed by disk storage or off-heap-memory. It is a fast and easy to use embedded Java database engine.
ClickHouse - ClickHouse® is a free analytics DBMS for big data
oxigraph - SPARQL graph database
TileDB - The Universal Storage Engine