Index Structures for Main Memory Database Systems

Index Structures for Main Memory Database Systems

With the exponential growth of data available in the digital universe, having fast and space efficient access to data is increasingly becoming more and more important. At the same time, the amount of main memory have reached capacities that even large enterprise datasets can entirely be kept in RAM. To create state of the art data management systems, it is crucial to optimize those systems for modern hardware, in particular for concurrency, cache and space efficiency.
 

Team

Publications

2022

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Robert Binna, Eva Zangerle, Martin Pichl, Günther Specht and Viktor Leis: Height Optimized Tries. In ACM Trans. Database Syst., vol. 47, no. 1. Association for Computing Machinery, 2022

2018

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Robert Binna, Eva Zangerle, Martin Pichl, Günther Specht and Viktor Leis: HOT: A Height Optimized Trie Index for Main-Memory Database Systems. In Proceedings of the 2018 International Conference on Management of Data (SIGMOD 2018), pages 521-534. ACM, 2018

2011

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Robert Binna, Wolfgang Gassler, Eva Zangerle, Dominic Pacher and Günther Specht: SpiderStore: A Native Main Memory Approach for Graph Storage. In Proceedings of the 23nd Workshop Grundlagen von Datenbanken (GvDB 2011), Obergurgl, Austria. CEUR-WS.org, ISSN 1613-0073, Vol. 733, 2011.

2010

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Robert Binna, Wolfgang Gassler, Eva Zangerle, Dominic Pacher and Günther Specht: SpiderStore: Exploiting Main Memory for Efficient RDF Graph Representation and Fast Querying. In Proceedings of the 1st International Workshop on Semantic Data Management (SemData) at the 36th International Conference on Very Large Data Bases (VLDB 2010), Singapore. CEUR-WS.org, 2010.