7-Zip-zstd VS RocksDB

Do you consider rar a standard? It's a pretty good format, even though there aren't any good open-source implementations. But if you're willing to pay for your software, WinRAR command line versions are available for most platforms.

7zip is the most obvious free alternative. There is also a 7zip fork that offers zstd [1]. The command line experience for 7zip isn't very good however.

1: https://github.com/mcmilk/7-Zip-zstd

Check out https://github.com/mcmilk/7-Zip-zstd

There's also this fork which supports additional compressions: https://github.com/mcmilk/7-Zip-zstd

7-zip is actually not a bad option, but I'd strongly advise using the fast-lzma2 codec, because, well, it is waay faster, and might even give you better ratios, depending on how you use it. You can find an implementation here, and it is compatible with traditional 7-zip (you can decompress it on any computer with any newish version of 7z)

Hi, PeaZip can use McMilk's additional compression codecs for 7z format (Zstandard, Brotli, Lizard, etc), https://github.com/mcmilk/7-Zip-zstd

You can extract the files yourself with 7Zip. You can install 7Zip from here and then install this plugin to extract ZStandard files, or you can directly install the modified 7Zip with the plugin already from that plugin page. Then simply open the zst file you downloaded with 7Zip and extract it.

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.

[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)

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.

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.

I was looking at https://github.com/facebook/rocksdb/ but it seems to not allow queries by value, as my last requirmenet.

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...

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.

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.

https://github.com/facebook/rocksdb/issues?q=is%3Aissue+clic...

Here are some bugs in JeMalloc: