Current database systems were designed assuming that data resides on disk. This assumption is no longer valid; main memories have become sufficiently large that most OLTP databases can reside entirely in memory. In this project we investigate what architectural changes and new techniques are required to realize the potential for great performance improvements offered by storing data in main memory.
- Ahmed Eldawy, Justin Levandoski, and Paul Larson, Trekking Through Siberia: Managing Cold Data in a Memory-Optimized Database, in International Conference on Very Large Databases (PVLDB Vol. 7, Issue. 11), June 2014, VLDB – Very Large Data Bases, September 2014
- Justin Levandoski, David Lomet, Sudipta Sengupta, Adrian Birka, and Cristian Diaconu, Indexing on Modern Hardware: Hekaton and Beyond , in Proceedings of the ACM SIGMOD International Conference on Management of Data, SIGMOD 2014 , ACM, June 2014
- Karolina Alexiou, Donald Kossmann, and Per-Ake Larson, Adaptive Range Filters for Cold Data: Avoiding Trips to Siberia, VLDB – Very Large Data Bases, September 2013
- Cristian Diaconu, Craig Freedman, Erik Ismert, Per-Ake Larson, Pravin Mittal, Ryan Stonecipher, Nitin Verma, and Mike Zwilling, Hekaton: SQL Server’s Memory-Optimized OLTP Engine, ACM International Conference on Management of Data, 22 June 2013
- Justin Levandoski, David Lomet, and Sudipta Sengupta, The Bw-Tree: A B-tree for New Hardware, in 2013 IEEE 29th International Conference on Data Engineering (ICDE), International Conference on Data Engineering, 8 April 2013
- Justin J. Levandoski, Per-Ake Larson, and Radu Stoica, Identifying Hot and Cold Data in Main-Memory Databases, in 2013 IEEE 29th International Conference on Data Engineering (ICDE), International Conference on Data Engineering, 8 April 2013
- Per-Åke Larson, Spyros Blanas, Cristian Diaconu, Craig Freedman, Jignesh Patel, and Mike Zwilling, High-Performance Concurrency Control Mechanisms for Main-Memory Databases, in PVLDB Vol 5(4), Very Large Data Bases Endowment Inc., December 2011