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
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.
MonetDB Solutions ontvangt investering van ServiceNow
MonetDB Solutions, opgericht door onderzoekers van Centrum Wiskunde & Informatica (CWI), maakt vandaag bekend dat het een investering ontvangt van het Amerikaanse servicemanagement-bedrijf ServiceNow.
Responsible use of Data key theme in successful SIGMOD/PODS 2019 Amsterdam
Drawing over 1000 visitors and record industry sponsorship, this year’s edition of the ACM SIGMOD/PODS conference turned Amsterdam into the world’s hotspot for data management research. The week-long conference on one evening also featured the biggest ever Amsterdam Data Science (ADS) meetup for local data scientists.
Members
Associated Members
Publications
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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.
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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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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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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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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
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