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
Making a tedious search a breeze: parallel query execution in multi-core systems
When you request information from a huge database, you might want to grab a cup of coffee and sit back, because your request may take a while. How can we optimize searches for information, specifically in a multi-core processing unit? The answer may lie in parallel queries, which run simultaneously on different processors.
Martin Kersten appointed ACM Fellow
CWI fellow Martin Kersten has been appointed as one of the 2016 fellows of the Association of Computing Machinery (ACM).
CWI develops new tools for data exploration
PhD student Thibault Sellam from CWI developed new tools to explore large databases. It allows explorative users to find interesting information hidden inside a database, with little or no knowledge of the data beforehand.
Members
- George Anastasiou
- Jayme Bird
- Peter Boncz
- Georgiana Ciocirdel
- Richard Gankema
- Tim Gubner
- Pedro Holanda
- Laura Ionel
- Radu Jica
- Martin Kersten
- Benno Kruit
- Dean De Leo
- Stefan Manegold
- Tina Marjanov
- Sjoerd Mullender
- Hannes Mühleisen
- Niels Nes
- Mark Raasveldt
- Marta Radziszewska
- Nina Stijepovic
- Diego Tomé
- Mihai Varga
Associated Members
Publications
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Angles Rojas, R, Arenas, M, Barceló, P, Boncz, P.A, Fletcher, G, Gutierrez, C, … Voigt, H. (2018). G-CORE a core for future graph query languages. In Proceedings of the ACM SIGMOD International Conference on Management of data.
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Kipf, A, Lang, H, Pandey, V.N, Persa, R, Boncz, P.A, Neumann, T, & Kemper, A. (2018). Adaptive geospatial joins for modern hardware.
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Boncz, P.A, Anatiotis, A.-C, & Kläbe, S. (2017). JCC-H: Adding Join Crossing Correlations with skew to TPC-H. In Performance Evaluation and Benchmarking for the Analytics Era (pp. 103–119). doi:10.1007/978-3-319-72401-0_8
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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 (pp. 1022–1033).
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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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Rozenberg, E, & Boncz, P.A. (2017). Faster across the PCIe bus: A GPU library for lightweight decompression including support for patched compression schemes. In Proceedings of the International Workshop on Data Management on New Hardware. doi:10.1145/3076113.3076122
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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.
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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Capturing the Laws of Data Nature
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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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LAD: Layered Astronomical Databases (LAD)
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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)
Related partners
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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