Database Paper Browser

Back to papers

ODYS: An Approach to Building a Massively-Parallel Search Engine Using a DB-IR Tightly-Integrated Parallel DBMS for Higher-Level Functionality

Summary: ODYS builds a massively-parallel search engine atop a tightly integrated DBMS-IR, delivering SQL-like programming for IR workloads over a DBMS rather than a filesystem. A hybrid analytic-experimental model shows ~2% error and scalable performance (1B queries/day on 30B pages; 194 ms, 148 ms with 2× nodes), proving DBMS-driven search viability. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4723
Venue
SIGMOD
Year
2013
Pagerank
4.1945683e-05
Overall Rank
12,055 | 16.14%
DOI
-

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

Incoming Citations (Sorted by Pagerank)

Showing 0 of 0 citing papers.

Rank Citing Paper Year Venue Pagerank
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 1 of 1 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
157 HadoopDB: An Architectural Hybrid of MapReduce and DBMS Technologies for Analytical Workloads 2009 VLDB 0.00040397359
Previous Page 1 / 1 Next

Semantically Similar Papers