A framework for SQL-based mining of large graphs on relational databases

Sriganesh Srihari, Shruti Chandrashekar, Srinivasan Parthasarathy

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Citations (Scopus)


We design and develop an SQL-based approach for querying and mining large graphs within a relational database management system (RDBMS). We propose a simple lightweight framework to integrate graph applications with the RDBMS through a tightly-coupled network layer, thereby leveraging efficient features of modern databases. Comparisons with straight-up main memory implementations of two kernels - readth-first search and quasi clique detection - reveal that SQL implementations offer an attractive option in terms of productivity and performance.

Original languageEnglish
Title of host publicationAdvances in Knowledge Discovery and Data Mining - 14th Pacific-Asia Conference, PAKDD 2010, Proceedings
Number of pages8
EditionPART 2
Publication statusPublished or Issued - 2010
Externally publishedYes
Event14th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2010 - Hyderabad, India
Duration: 21 Jun 201024 Jun 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume6119 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other14th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2010


  • Graph mining
  • Relational databases
  • SQL-based approach

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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