Description
Leader of the group Database Architectures: Stefan Manegold.
We, the Database Architectures (DA) research group of CWI, are well known as a leading data systems research group, active in the broad area of analytical database management systems. Our research group has a strong international reputation in academia and industry for pioneering column store technology, fast compression methods, vectorized query execution, indexes for interactive data analysis, and analytical in-process database systems. We have spawned multiple spin-off companies (Data Distilleries, VectorWise, MonetDB Solutions, and DuckDB Labs). We pride ourselves on revealing the real problems in our discipline and coming up with revolutionary solutions that are frequently ahead of their time.
Vacancies
No vacancies currently.
News

Stefan Manegold wins 2020 SIGMOD Contributions Award
CWI researcher Stefan Manegold has been awarded the 2020 SIGMOD Contributions Award. The award recognizes his innovative work in the data management community to encourage scientific reproducibility.

Meet Turing Award winner Michael Stonebraker at ADS Meetup
In the wake of the Conference on Innovative Data Systems Research (CIDR), several of its high-profile participants will speak at a special public meetup “ADS Meets CIDR”.

CWI research collaboration leads to 100 million euro investment in Amsterdam
CWI’s research partner Databricks announced it will invest 100 million euros to expand its Amsterdam office. The company aims to grow to hundreds of R&D engineers. Databricks settled in Amsterdam nearly three years ago because of its research collaboration with CWI.

MonetDB Solutions secures investment from ServiceNow
MonetDB Solutions, a company formed by researchers at CWI, announces an investment from digital workflow company ServiceNow to help large enterprises drive digital transformation.
Members
Associated Members
Publications
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Hinkel, G, Garcia-Dominguez, A, Schöne, R, Boronat, A, Tisi, M, Le Calvar, T, … Szárnyas, G. (2021). A cross-technology benchmark for incremental graph queries. Software and Systems Modeling. doi:10.1007/s10270-021-00927-5
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Holanda, P.T. (2021, September 21). Progressive indexes. SIKS Dissertation Series.
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Gubner, T.K, & Boncz, P.A. (2021). Charting the design space of query execution using VOILA. In Proceedings of the VLDB Endowment (pp. 1067–1097). doi:10.14778/3447689.3447709
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Gubner, T.K, & Boncz, P.A. (2021). Highlighting the performance diversity of analytical queries using VOILA. In Proceedings of the International Workshop on Accelerating Analytics and Data management Systems Using Modern Processor and Storage Architectures.
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Szárnyas, G, Bader, D.A, Davis, T.A, Kitchen, J, Mattson, T.G, McMillan, S, & Welch, E. (2021). LAGraph: Linear algebra, network analysis libraries, and the study of graph algorithms. In IEEE International Parallel and Distributed Processing Symposium Workshops (pp. 243–252). doi:10.1109/IPDPSW52791.2021.00046
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Mhedhbi, A, Lissandrini, M, Kuiper, L.N, Waudby, J, & Szárnyas, G. (2021). LSQB: A large-scale subgraph query benchmark. Proceedings of the ACM SIGMOD Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA), 8.1–8.11. doi:10.1145/3461837.3464516
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Kruit, B.B, Boncz, P.A, & Urbani, J. (2021). TAKCO: A platform for extracting novel facts from tables. In Companion of the World Wide Web Conference (pp. 705–707). doi:10.1145/3442442.3458611
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Lang, H, Beischl, A, Leis, V, Boncz, P.A, Neumann, T, & Kemper, A. (2020). Tree-Encoded Bitmaps. In Proceedings of the ACM SIGMOD International Conference on Management of Data (pp. 937–967). doi:10.1145/3318464.3380588
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Raasveldt, M. (2020, June 9). Integrating analytics with relational databases. SIKS Dissertation Series.
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Ghita, B, Gomes Tomé, D, & Boncz, P.A. (2020). White-box compression: Learning and exploiting compact table representations. In Proceedings of the Conference on Innovative Data Systems Research.
Software
MonetDB: high-performance query processing against very large databases
MonetDB is a relational database management system (DBMS) providing high performance on complex queries against large databases.
Current projects with external funding
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RelationalAI-CWI Research Agreement ()
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Actian Research Grant II (ACTIAN II)
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Cross-Industry Predictive Maintenance Optimization Platform (CIMPLO)
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Databricks CWI Research Agreement (Databricks)
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Databricks III
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Lokale Digitale Competentie centra (DCC) (DCC-NWO-I)
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Facebook Research Grant (Facebook)
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Velox Optimizations and supporting new file formats (Meta)
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Research agreeement CWI - Databricks - vervolg contract (None)
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RelationalAI-CWI Research Grant Agreement (RelationalAI)
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Structure-aware Querying & Information Retrieval on Evolving Large Graphs (SQIREL-GRAPHS)
Related partners
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Actian Corporation
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Databricks
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LIACS Institute
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Neo Technology AB
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OBI4wan B.V.
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RelationalAI
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Spinque
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WizeNoze B.V.
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Facebook
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Meta Platforms Inc