Data Management
The Data Management Lab was founded in 2017 by Prof. Carsten Binnig and is part of the Department of Computer Science at TU Darmstadt in Darmstadt, Germany.
TU Darmstadt is one of the leading technical universities in Germany. Its Computer Science department consistently ranks among the top 5 in Germany. TU Darmstadt offers a unique environment for research in data management due to strong cooperations with other groups like the Machine Learning Lab or Distributed Systems Programming Lab, as well as ample interdisciplinary interaction.
Our lab page lists all team members. Please see our job listings if you are interested in working with us.
Research
We conduct research in several areas of databases and data management in conjunction with artificial intelligence (AI). The groups main focus areas are Systems for AI and AI for Systems.
Teaching
Our lab regularly offers courses, seminars and labs on various data management topics. Furthermore, we offer term projects and Bachelors and Masters thesis projects with different focus areas.
News
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2019/07/01
Our paper “High-Performance In-Network Data Processing” was accepted for the Tenth International Workshop at ADMS 2019/VLDB 2019
As a first contribution of this paper, we propose a new switch architecture that can be employed as an in-network co-processor for analytical SQL workloads.
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2019/07/01
Best Student Paper Award for our paper “XAI – A Middleware for Scalable AI” which was accepted to Data 2019
Abdallah Salama received the Best Student Paper Award for his paper “XAI – A Middleware for Scalable AI” which runs on top of existing deep learning frameworks such as TensorFlow or MXNet and automates the hyper-parameter search for distributed deep
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2019/07/01
Our paper “BlockchainDB A – Shared Database on Blockchains” was accepted to VLDB 2019
We present BlockchainDB, which leverages blockchains as a storage layer and more..
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2019/07/01
Our paper “DBPal: Weak Supervision for Learning a Natural Language Interface to Databases” was accepted for the “Conversational Access to Data (CAST) Workshop” at VLDB 2019
A new system to translate natural language utterances into SQL statements using a neural machine translation model
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2019/06/12
Our paper “Model-based Approximate Query Processing” was accepted to AIDB workshop at VLDB 2019
New approach to Approximate Query Processing (AQP) called Model-based AQP