[wswope]

SQLite is what you're looking for. If you want to use the CLI,

  .format csv
  .import <path to csv file> <table name>

Alternatively, read your data into pandas and there's extremely easy interop between a DBAPI connection from the python standard lib Sqlite3 module and Pandas (to_sql, read_sql_query, etc.).

[thamer]

I would second this suggestion. I was querying CSV data imported into SQLite this weekend, and it was extremely easy to get started. SQLite is pretty snappy even for tables with millions of rows.

SQLite supports defining columns without a type and will use TEXT by default, so you can take the first line of your CSV that lists the document's dimensions, put those in the brackets of a CREATE TABLE statement, and then run the .import described above (so just CREATE TABLE foo(x,y,z); if x,y,z are your column names).

After importing the data don't forget to create indexes for the queries you'll be using most often, and you're good to go.

Another suggestion for once your data is imported, have SQLite report it in table format:

    .mode column
    .headers on