Today Julia Computing is excited to announce JuliaDB.jl ( https://github.com/JuliaComputing/JuliaDB.jl ), a package for working with large persistent data sets. It is still at a fairly early stage, but we wanted to release it as soon as we had meaningful functionality. JuliaDB ties together several e…

[image] davidanthoff: I’m not sure the name helps here, maybe at least add the word distributed somehow, that seems really the core idea here? That’s why it’s called Julia Distributed Bytes :slight_smile:

We’re working on benchmarks; some will be posted fairly soon. It would definitely be good to support more file formats, especially feather and parquet. So far we get a small amount of compression from PooledArrays (for columns with few unique values), but this is also something we’ll keep working o…

Don’t forget fst and feather. Any non-official previous results?

Don’t forget fst and feather. Fair enough, but they correspond only to a part of JuliaDB.jl’s functionality, namely serialization and deserialization.

Does fst exist as a file storage format outside of the R package http://www.fstpackage.org/ ? I got the impression from the documentation that the file storage format is not documented other than in the code and that it is subject to change. Specifically, the page states Note to users: The binary …

[image] shashi: The candidates for comparison we are considering are pandas.Series and xts, (maybe also data.table) which are columnar in-memory databases in the same design space as JuliaDB.jl, rather than sqlite. Comparing IndexedTables.jl with pandas seems to make a lot of sense, but the s…

Currently the way JuliaDB handles distributed datasets and storage is pretty tied to the index concept, so it’s related. I would be fine with a non-descriptive name if we can think of a good one.

Yes, we can only fairly compare single-process performance. The idea is to get to within reasonable speed of pandas including whatever overhead comes from wrapping IndexedTables.jl with Dagger.jl’s scheduler on a single process, and then demonstrate some speed ups vs single process performance with …

Why single-core? Do you mean single core or single thread?

Because I believe pandas, for example, doesn’t come with multi-processing/multi-threading.

ANN: JuliaDB.jl

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ChrisRackauckas May 8, 2017, 5:10pm 11

That’s why it’s called Julia Distributed Bytes

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ANN: JuliaDB.jl

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