Welcome to my field notes!

Field notes are notes I leave myself as I go through my day to day work. The hope is that other people will also find these notes useful. Note that these notes are unfiltered and unverified.

Databases in Julia

Source: scripts/Database.jl Using: LibPQ.jl, Octo.jl, Stipple.jl

  • My favorite database is PostgreSQL, so I decided to see how I can access this database.
  • There’s a standard interface for connecting to databases, but sadly that doesn’t seem to be available for Postgres, instead I’m redirected to the libpq interface LibPQ.jl


  • Is there something more high level that I can use?


  • With this, I’m able to to make queries and execute them, it’s quite low level but it works for my standard Postgres installation.
  • I’m able to transpose this into a DataFrame. I don’t quite understand the many different tabular structures yet (I’m used to the built-in dataframe in R), but I can see how that works. See Data Frames.


  • DDL Statements have to be written manually
  • Transactions have to be written manually (but easily wrapped)
  • Yes I can insert stuff, but still need SQL knowledge


  • This is a more standard interface, but it’s less feature rich. I’m skipping this for now but this might be the way to get to lesser known DBs.


  • It’s a SQL Query DSL in Julia. Amazing, is this going to be like the {dbplyr} package in R? Making a decent data access layer is soooooo hard!
  • Okay so now I have to actually use structs
  • It supports Postgres, and MySQL and SQLite too!
  • Okay I was able to query the information schema using a basic query tool. I’m really not sure why I have to define a struct
  • Really these function documentations are a little over my head: for example: Schema.model( will surface CoreType where T or something which does not really give me information about what arguments to place). May just be that we need to add more docstrings or something?
  • SQL keywords in the DSL part need to be capitalized
  • I was able to query a bit and get in tune with the DSL, seems ok as a web app backend ORM but not for data analysis.


The package currently provides working implementations for in-memory data sources, but will eventually be able to translate queries into e.g. SQL. There is a prototype implementation of such a “query provider” for SQLite in the package, but it is experimental at this point and only works for a very small subset of queries.

This one is super promising but isn’t implemented yet.