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.

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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

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.

Making a tedious search a breeze: parallel query execution in multi-core systems - Read More…

Current events

1st International Conference on Big Scientific Data Management (BigSDM2018)

  • 2018-11-30T08:30:00+01:00
  • 2018-12-01T18:30:00+01:00
November 30 Friday

Start: 2018-11-30 08:30:00+01:00 End: 2018-12-01 18:30:00+01:00

Beijing, China

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                                 CALL FOR PAPERS
 
 1st International Conference on Big Scientific Data Management (BigSDM2018)
 
                       http://bigsdm2018.csdata.org
                  Nov. 30 - Dec. 1, 2018, Beijing, China
           Submission Deadline: September 15th, 2018 (Abstract)
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 The 1st International Conference on Big Scientific Data Management (BigSDM  2018) will be held in Beijing, China from Nov. 30th to Dec 1st, 2018. The  Conference is jointly organized by Chinese Academy of Sciences, Peking  University, Tsinghua University, Renmin University of China, CWI and MonetDB  Solutions.
 
 The theme of BigSDM 2018 is data-driven scientific discovery. The conference  aims at bring together international experts from natural and computer sciences  to explore the life-cycle management of Big Scientific Data, to discuss major  methodologies and key technologies in Big Data-driven discovery making, to  exchange experience and knowledge about Big Scientific Data across various  fields through specific cases, and to identify the challenges and opportunities  in scientific discovery acceleration. We hope to, through the conference,  gather ideas for fostering new ways of scientific thinking, and promote big  data sciences at large.
 
 The program of BigSDM 2018 features several keynote talks by famous experts in  the important areas of big data sciences. We have invited Barry C. Barish, the  winner of 2017 Nobel Prize in Physics, Huadong Guo who is an Academician of  Chinese Academy of Sciences, and Alexander S. Szalay, the bloomberg  distinguished professor from the Johns Hopkins University to share their  cutting edge technology and views about the big scientific data management. In  the meantime, we are about to invite the principal researchers from major  scientific experiments, such as the Five- hundred-meter Aperture Spherical  radio Telescope (FAST), and major data projects, such as 'CASEarth' in China to  share their experiences in data-driven scientific discovery. 'CASEarth' is a  CAS Strategic Pioneering Research and Development Programme, focusing on  building a global big data network to study Earth and support research on  climate change, as well as to predict and mitigate natural disasters. The other  events include topic-specific forums and lightning talks.
 
 BigSDM 2018 welcomes researchers, professionals, practitioners, and officers  worldwide in related areas to submit papers and attend the conference.

Members

Associated Members

Publications

Software

Current projects with external funding

  • Actian CWI Research Grant
  • Capturing the Laws of Data Nature
  • Cross-Industry Predictive Maintenance Optimization Platform (CIMPLO)
  • Data Mining on High Volume Simulation Output (DAMIOSO)
  • Databricks CWI Research Agreement (Databricks)
  • LAD: Layered Astronomical Databases (LAD)
  • Process mining for multi-objective online control (PROMIMOOC)
  • The SciLens-II Infrastructure, Big Data at work (Scilens-II)
  • Structure-aware Querying & Information Retrieval on Evolving Large Graphs (SQIREL-GRAPHS)

Related partners

  • Actian Corporation
  • BMW Munich
  • Databricks
  • LIACS Institute
  • MonetDB B.V.
  • Neo Technology AB
  • OBI4wan B.V.
  • Spinque
  • Tata Steel
  • WizeNoze B.V.