leveldb

Chrome has LevelDB (which is awesome!) on the backend but the result isn't much faster in my experience.

LevelDB is only used for indexes to look up series files by sets of dimensions, not for time-based lookups.

It is using LevelDB under the hood for storing the data on disk and it is written in C++.

Now there's LevelDB and its SSTable is sort of close but uses Snappy so it can't operate on compressed data.

Google screwed this up badly with LevelDB which had(still has?) horrible performance issues caused by compaction.

Users that wanted to could run the app full-time on their local machine, where the database would be leveldb instead of IndexedDB.

Only then do we actually start loading any actual time series data (not from LevelDB this time).

As a simple example, we have one LevelDB index which has single label=value pairs as the keys and as the LevelDB value, the identifiers of the time series which have those label=value dimensions.

On the other hand, the data structures you query in real-time, making that immutable is problematic, because then you'll need a LevelDB style compaction step.

The built-in compression of LevelDB tables is also a boon here...

LevelDB also battle tested lots of systems build on it.

A much more sensible set of tradeoffs than LevelDB.