An Architectural Hybrid of MapReduce and DBMS Technologies for Analytical Workloads.
For more detail, check out the
DBMS Musings blog post, or the paper below.
- A hybrid of DBMS and MapReduce technologies that targets analytical workloads
- Designed to run on a shared-nothing cluster of commodity machines, or in the cloud
- An attempt to fill the gap in the market for a free and open source parallel DBMS
- Much more scalable than currently available parallel database systems and DBMS/MapReduce hybrid systems.
- As scalable as Hadoop, while achieving superior performance on structured data analysis workloads
HadoopDB: An Architectural Hybrid of MapReduce and DBMS Technologies for Analytical Workloads. Azza Abouzeid, Kamil Bajda-Pawlikowski, Daniel J. Abadi, Avi Silberschatz, Alex Rasin. In Proceedings of VLDB, 2009. [PDF]
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HadoopDB Team 2009