Description
Leader of the group Database Architectures: Stefan Manegold.
We are a top database systems research group, active in the broad area of data management systems and infrastructure for supporting data science. Our 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 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. We also operate 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
Stefan Manegold appointed professor at Leiden University
Starting from 15 September 2014, Stefan Manegold, of the Centrum Wiskunde & Informatica (CWI) in Amsterdam, has been appointed Professor for Data Management at the Faculty of Science of Leiden University.
International innovation award to Martin Kersten
Martin Kersten, Research fellow at the Centrum Wiskunde & Informatica (CWI) is awarded the 2014 SIGMOD Edgar F. Codd Innovations Award, the most prestigious prize for researchers who have made innovative and significant contributions to database systems and databases.
Database Indexes for the Big Data Era
Researchers of Centrum Wiskunde & Informatica (CWI) in Amsterdam have developed new methods to index huge databases. These space efficient indexes are lightweight to build and maintain and grow less than linear with the size of the data sets.
Members of Database Architectures
Publications
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Raasveldt, M, & Mühleisen, H.F. (2017). Don't hold my data hostage - A case for client protocol redesign. In Proceedings of the VLDB Endowment.
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Sidirourgos, E, & Mühleisen, H.F. (2017). Scaling column imprints using advanced vectorization. Presented at the Thirteenth International Workshop on Data Management on New Hardware. doi:10.1145/3076113.3076120
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CWI gaat samenwerking aan met Databricks - executive-people.nl - 29-04-2017. (2017). CWI gaat samenwerking aan met Databricks - executive-people.nl - 29-04-2017.
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Database-onderzoek en vooruitlopen op de toekomst - computable.nl - 25-04-2017. (2017). Database-onderzoek en vooruitlopen op de toekomst - computable.nl - 25-04-2017.
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CWI en Databricks gaan samenwerken - engineerslonline.nl - 25-04-2017. (2017). CWI en Databricks gaan samenwerken - engineerslonline.nl - 25-04-2017.
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Database-onderzoek en voorlopen op de toekomst - Computable - 31-03-2017. (2017). Database-onderzoek en voorlopen op de toekomst - Computable - 31-03-2017.
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Database-onderzoek en voorlopen op de toekomst - Computable - 31-03-2017. (2017). Database-onderzoek en voorlopen op de toekomst - Computable - 31-03-2017.
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Gawade, M.M. (2017, February 15). Multi-core parallelism in a column-store. SIKS Dissertation Series.
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Mühleisen, H.F, Bertram, A, & Kallen, M-J. (2017). Database-Inspired Optimizations for Statistical Analysis. Journal of Statistical Software.
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CWI'er Martin Kersten is benoemd tot ACM Fellow 2016 - Computable -12-12-16. (2016). CWI'er Martin Kersten is benoemd tot ACM Fellow 2016 - Computable -12-12-16.
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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Actian CWI Research Grant
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Capturing the Laws of Data Nature
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CIMPLOCross-Industry Predictive Maintenance Optimization Platform
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DAMIOSOData Mining on High Volume Simulation Output
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DatabricksDatabricks CWI Research Agreement
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LADLAD: Layered Astronomical Databases
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PROMIMOOCProcess mining for multi-objective online control
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Scilens-IIThe SciLens-II Infrastructure, Big Data at work
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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Tata Steel