Commoditizing Data Analytics in the Cloud

The goal of this ERC-funded project is to commoditize large-scale data analytics in the cloud.
As a commodity, data analytics should be as cheap and readily available as electricity, meaning:

The cost of analytics should be close to the theoretical minimum: the hardware cost.
Data can be moved easily between clouds and systems.

To achieve this, we are designing and developing an open and cost-efficient analytical data analytics system for the cloud.

Team

Prof. Viktor Leis, Maximilian Kuschewski, Till Steinert, Pascal Ginter

Publications

Venue	Publication	Link
SIGMOD 2025	High-Performance Query Processing with NVMe Arrays: Spilling without Killing Performance Maximilian Kuschewski, Jana Giceva, Thomas Neumann, Viktor Leis	pdf
CIDR 2024	A Critique of Modern SQL And A Proposal Towards A Simple and Expressive Query Language Thomas Neumann, Viktor Leis	pdf code demo
SIGMOD 2023	BtrBlocks: Efficient Columnar Compression for Data Lakes Maximilian Kuschewski, David Sauerwein, Adnan Alhomssi, Viktor Leis	pdf code
VLDB 2023	Cloud Analytics Benchmark Alexander van Renen, Viktor Leis	pdf code
VLDB 2021	Towards Cost-Optimal Query Processing in the Cloud Viktor Leis, Maximilian Kuschewski	pdf code

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I13/DIS - Chair for Decentralized Information Systems and Data Management

Prof. Dr. Viktor Leis

Technical University of Munich
Boltzmannstr. 3
85748 Garching
Germany

sekretariat@dis.cit.tum.de
phone: +49 (89) 289 18486

Funded by the ERC

Funded by the European Union (ERC, CODAC, 101041375). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Council Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.