From the webpage:
Introduction
Tajo is a relational and distributed data warehouse system for Hadoop. Tajo is designed for low-latency and scalable ad-hoc queries, online aggregation and ETL on large-data sets by leveraging advanced database techniques. It supports SQL standards. Tajo uses HDFS as a primary storage layer and has its own query engine which allows direct control of distributed execution and data flow. As a result, Tajo has a variety of query evaluation strategies and more optimization opportunities. In addition, Tajo will have a native columnar execution and and its optimizer.
Features
- Fast and low-latency query processing on SQL queries including projection, filter, group-by, sort, and join.
- Rudiment ETL that transforms one data format to another data format.
- Support various file formats, such as CSV, RCFile, RowFile (a row store file), and Trevni.
- Command line interface to allow users to submit SQL queries
- Java API to enable clients to submit SQL queries to Tajo
If you ever wanted to get in on the ground floor of a data warehouse project, this could be your chance!
I first saw this at Apache Incubator: Tajo – a Relational and Distributed Data Warehouse for Hadoop by Alex Popescu.