StarDB: A Large-Scale DBMS for Sequences

Sequences and applications using them are proliferating in science and business. Currently, sequences are stored in file systems and processed using ad-hoc procedural code. Existing techniques are not flexible and cannot efficiently handle complex queries or large datasets. In this paper, we demonstrate StarDB, a distributed database system for analytics on sequences. StarDB hides data and system complexities and allows users to focus on analytics. It uses a comprehensive set of parallel string operations and provides a declarative query language to solve complex queries. StarDB automatically tunes itself and runs with over 90\% efficiency on supercomputers, public clouds, clusters, and workstations. We test StarDB using real datasets that are 2 orders of magnitude larger than the datasets reported by previous works.


Relevant publications:
Majed Sahli, Essam Mansour, Panos Kalnis. StarDB: A Large-Scale DBMS for Strings. PVLDB 8(12): 1844-1855 (2015)​