Description
Leader of the group Database Architectures: Stefan Manegold.
We, the Database Architectures (DA) research group of CWI, are well known as a top data systems research group, active in the broad area of data (management) systems and infrastructure for supporting data science. Our research group has a strong international reputation in academia and industry for pioneering column store technology, fast compression methods, vectorized query execution, on-line query-driven indexing (cracking), adaptive caching, and integration of statistical languages and analysis in database management systems.
We develop, distribute and maintain the MonetDB open-source system, and we have spawned multiple spin-off companies, including Data Distilleries, VectorWise and MonetDB Solutions. Our team also operates a self-built cluster, SciLens, that – unlike many other computer clusters – is bandwidth-optimized and thus better suited as a data-science infrastructure. 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
PhD Students in the areas of Big Data Management and Analysis Architectures and Data Science Engineering Technologies
Three fully funded PhD positions are available to work under the direction of prof. Stefan Manegold on big data management technology with a particular focus on hardware-conscious data structures and algorithms in distributed and cloud environments as well as the integration of data mining and machine learning into large-scale data management systems.
News
Mark Raasveldt wins Student Research Competition at SIGMOD 2018
Mark Raasveldt, PhD student at CWI’s Database Architecture (DA) group, won the Student Research Competition at the SIGMOD 2018 conference for his work titled "MonetDBLite: An Embedded Analytical Database".
Hardman new chair Amsterdam Data Science, Boncz joins Supervisory Board
As of January 2018, CWI researcher Lynda Hardman is the new chair of the management team of Amsterdam Data Science. Peter Boncz, CWI researcher and part of the CWI management team, will join the ADS Supervisory Board.
CWI Database Architecture researchers awarded with best paper runner up award at SSDBM
Researchers of CWI's Database Architecture group have been awarded with a best paper runner up award at 29th International Conference on Scientific and Statistical Database Management (SSDBM 2017) in Chicago. The researchers received the award for their paper 'Multi Hypothesis CSV-parsing' by authors Till Döhmen, Hannes Mühleisen and Peter Boncz.
CWI en Databricks lanceren samenwerking in aanwezigheid van minister Kamp
Op 25 april 2017 lanceren CWI en het big data analyse- en data science software-bedrijf Databricks een nieuwe samenwerking. Dat gebeurt bij de Hannover Messe, in aanwezigheid van Minister Kamp van Economische Zaken.
Current events
PhD defense Mark Raasveldt (Database Architectures)
- 2020-06-09T11:15:00+02:00
- 2020-06-09T13:15:00+02:00
PhD defense Mark Raasveldt (Database Architectures)
Start: 2020-06-09 11:15:00+02:00 End: 2020-06-09 13:15:00+02:00
Everyone is invited to attend the public "online"defense of Mark Raasveld on June 9th 2020.
Title: Integrating Analytics with Relational Databases
Promotor: Prof. dr. Stefan Manegold (CWI/UL)
Copromotor: Dr. Hannes Mühleisen (CWI)
University: Leiden University
Link to attend the defense will be available as soon as possible
- Email: Mark Raasveldt
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iCal
Members
Associated Members
Publications
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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.
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Kipf, A, Lang, H, Pandey, V.N, Persa, R.A, Anneser, C, Zacharatou, E.T, … Kemper, A. (2020). Adaptive main-memory indexing for high-performance point-polygon joins. In Advances in Database Technology - EDBT (pp. 347–358). doi:10.5441/002/edbt.2020.31
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Gubner, T.K, Gomes Tomé, D, Lang, H, & Boncz, P.A. (2019). Fluid co-processing: GPU Bloom-filters for CPU joins. In Proceedings of the 15th International Workshop on Data Management on New Hardware (pp. 9:1–9:10). doi:10.1145/3329785.3329934
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Kipf, A, Vorona, D., Müller, J, Kipf, T, Radke, B, Leis, V, … Kemper, A. (2019). Estimating cardinalities with deep sketches. In Proceedings of the ACM SIGMOD International Conference on Management of Data (pp. 1937–1940). doi:10.1145/3299869.3320218
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De Leo, D, & Boncz, P.A. (2019). Fast concurrent reads and updates with PMAs. In Proceedings of the Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA) 2019. doi:10.1145/3327964.3328497
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Raasveldt, M, & Mühleisen, H.F. (2019). [Demo] DuckDB: An embeddable analytical database. In Proceedings of the ACM SIGMOD International Conference on Management of Data (pp. 1981–1984). doi:10.1145/3299869.3320212
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Boncz, P.A, Manegold, S, Ailamaki, A, Deshpande, A, & Kraska, T (Eds.). (2019). Proceedings of the 2019 International Conference on Management of Data. In P.A Boncz, S Manegold, A Ailamaki, A Deshpande, & T Kraska (Eds.), .
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Kersten, M.L, Koutsourakis, P, Manegold, S, & Zhang, Y. (2019). SQALPEL: A database performance platform. In CIDR 2019 - 9th Biennial Conference on Innovative Data Systems Research.
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Lang, H, Neumann, T, Kemper, A, & Boncz, P.A. (2019). Performance-Optimal Filtering:Bloom Overtakes Cuckoo at High Throughput. Proceedings of the VLDB Endowment, 502–515. doi:10.14778/3303753.3303757
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Mühleisen, H.F, Bertram, A, & Kallen, M-J. (2018). Database-inspired optimizations for statistical analysis. Journal of Statistical Software, 87(4). doi:10.18637/jss.v087.i04
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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Data Mining on High Volume Simulation Output (DAMIOSO)
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Databricks CWI Research Agreement (Databricks)
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Facebook Research Grant (Facebook)
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Min.VWS Bestrijding Covid-19
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Research agreeement CWI - Databricks - vervolg contract (None)
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Process mining for multi-objective online control (PROMIMOOC)
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The SciLens-II Infrastructure, Big Data at work (Scilens-II)
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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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BMW Munich
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Databricks
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LIACS Institute
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MonetDB B.V.
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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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Tata Steel
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WizeNoze B.V.
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Facebook
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Ministerie van Volksgezondheid, Welzijn en Sport