TenSQL: An SQL Database Built on GraphBLAS

Relational Database Management Systems (RDBMS) have been the most prominent form of database in the world for several decades. While relational databases are often applied within high-frequency/low-volume transactional applications such as website backends, the poor performance of relational databases on low-frequency/high-volume queries often precludes their application to big data analysis fields like graph analytics. This work explores the construction of an RDBMS solution that uses the GraphBLAS API to execute Structured Query Language (SQL) in an effort to improve performance on high-volume queries. Tables are redefined to be collections of sparse scalars, vectors, matrices, and more generally sparse tensors. The explicit values (nonzeros) in these sparse tensors define the rows and NULL values within the tables. A prototype database called TenSQL was constructed and evaluated against several SQL implementations including PostgreSQL. Preliminary results comparing the performance on queries common in graph analysis applications offer performance improvements as high as 1,400x over PostgreSQL for moderately sized datasets when returning results in a columnar format.