SQLite VS RocksDB

Oh that's a huge dick move. And this behaviour you mention, "people seeking help from libcurl for xcurl" is an already documented and detrimental problem. You can see why Sqlite temp files has an extension of "etilqs". That's a grandiose example of this. That was not even a documentation link!

https://github.com/mackyle/sqlite/blob/3cf493d/src/os.h#L52-...

I could set up a redirect to the '/raw/' pages but then the syntax highlighting is gone.

The same page is perfectly viewable over plain html on gothub[2] though.

Github also seems to be hiding their "Assets" (binaries et al) on the "/releases" page for some projects behind javascript(especially older versions).[3] Something else that wasn't the case about ~1.5 years ago.

Would be great if gothub could unshackle the links to those as well[4], but that appears to not be working at the moment[5] .

This project appears to be a more performant(measurably so), more privacy friendly(as Microsoft won't have a record of your interest in certain projects) alternative front-end for "non logged in" github users.

I like it, but it still needs work.

[1] https://github.com/mackyle/sqlite/blob/18cf47156abe94255ae14...

[2] https://gh.bloatcat.tk/mackyle/sqlite/blob/18cf47156abe94255...

[3] https://github.com/mikf/gallery-dl/releases

[4] https://gh.bloatcat.tk/mikf/gallery-dl/releases

[5] https://codeberg.org/gothub/gothub/issues/74

You can find details in official wiki in github https://github.com/facebook/rocksdb/wiki/Basic-Operations

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.