RocksDB
rqlite
RocksDB | rqlite | |
---|---|---|
43 | 112 | |
27,424 | 14,898 | |
0.8% | 0.9% | |
9.8 | 9.9 | |
3 days ago | 3 days ago | |
C++ | Go | |
GNU General Public License v3.0 only | MIT License |
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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:
rqlite
- The lightweight, easy-to-use, distributed relational database built on SQLite
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CursusDB – A new scalable distributed document oriented database
Seems like you could do the same with rqlite [1], since SQLite supports JSON.
[1]: https://rqlite.io
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Rqlite 8.0
rqlite[1] creator here, happy to answer any questions about rqlite, this latest release, and how it works.
[1] https://rqlite.io
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Adding new database engine support
I found simple distributed RQlite https://github.com/rqlite/rqlite based on raft and sqlite. How hard is to add it?
- I'm All-In on Server-Side SQLite
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So, you want to deploy on the edge?
rqlite[1] creator here, happy to answer any questions. rqlite also supports read-only nodes, which can also help with reads at the "edge". It probably wouldn't scale to 100s of nodes, it is an option.
"rqlite supports adding read-only nodes. You can use this feature to add read scalability to the cluster if you need a high volume of reads, or want to distribute copies of the data nearer to clients – but don’t want those nodes counted towards the quorum. These types of nodes are also known as non-voting nodes."
[1] https://rqlite.io/
[2] https://rqlite.io/docs/clustering/read-only-nodes/
- LiteFS Cloud: Distributed SQLite with Managed Backups
- Show HN: Rqlite, distributed DB built on SQLite, now runs on MIPS, RISC, PowerPC
- rqlite v7.19.0: the lightweight distributed relational database built on Go, Raft, and SQLite -- now runs on MIPS, PowerPC, and RISC
- rqlite v7.18: the lightweight distributed database built on Go, Raft, and SQLite -- now with new Unified HTTP endpoint for easy reads and writes
What are some alternatives?
LevelDB - LevelDB is a fast key-value storage library written at Google that provides an ordered mapping from string keys to string values.
dqlite - Embeddable, replicated and fault-tolerant SQL engine.
LMDB - Read-only mirror of official repo on openldap.org. Issues and pull requests here are ignored. Use OpenLDAP ITS for issues.
litestream - Streaming replication for SQLite.
SQLite - Unofficial git mirror of SQLite sources (see link for build instructions)
cockroach - CockroachDB - the open source, cloud-native distributed SQL database.
sled - the champagne of beta embedded databases
bolt
ClickHouse - ClickHouse® is a free analytics DBMS for big data
etcd - Distributed reliable key-value store for the most critical data of a distributed system [Moved to: https://github.com/etcd-io/etcd]
TileDB - The Universal Storage Engine
TinyGo - Go compiler for small places. Microcontrollers, WebAssembly (WASM/WASI), and command-line tools. Based on LLVM.