A column oriented, embarrassingly distributed, relational event database.

Features

• column oriented - super fast queries
• events - write only semantics
• distributed insert - designed for petabyte scale distributed datasets with massive write loads
• compressed - bitmap indexes, lz4, and prefix trie compression
• relational - join gigantic data sets
• partitioned - smart shards
• embarrassingly distributed (based on Disco)
• embarrassingly fast (uses LMDB)
• NoSQL - Python DSL
• bulk append only semantics
• highly available, horizontally scalable
• REPL/CLI query interface

Example Query

select(impressions.ad_id, impressions.date, h_sum(pix.amount), h_count(),
       where=((impressions.date < '2014-01-13') & (impressions.ad_id == 30010),
               pix.date < '2014-01-13'),
       join=(impressions.site_id, pix.site_id),
       order_by=impressions.date)

Installation

After cloning this repo, here are some considerations:

• you will need Python 2.7 or higher - note that it probably won't work on 2.6 (has to do with pickling lambdas...)
• you need to install Disco 0.5 and its dependencies - get that working first
• you need to install Hustle and its 'deps' thusly:

cd hustle
sudo ./bootstrap.sh

Please refer to the Installation Guide for more details

Documentation

Hustle User Guide

Hustle Mailing List

Credits

Special thanks to following open-source projects:

• EWAHBoolArray
• disco
• liblmdb
• lz4
• ultrajson

Build Status: Travis-CI ::