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08/07/2023
CAESURA: Language Models as Multi-Modal Query Planners
Traditional query planners translate SQL queries into query plans to be ...
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05/24/2023
Towards Foundation Models for Relational Databases [Vision Paper]
Tabular representation learning has recently gained a lot of attention. ...
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04/26/2023
Towards Multi-Modal DBMSs for Seamless Querying of Texts and Tables
In this paper, we propose Multi-Modal Databases (MMDBs), which is a new ...
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07/08/2022
Zero-Shot Cost Models for Distributed Stream Processing
This paper proposes a learned cost estimation model for Distributed Stre...
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07/04/2022
DiffML: End-to-end Differentiable ML Pipelines
In this paper, we present our vision of differentiable ML pipelines call...
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06/01/2022
P4DB – The Case for In-Network OLTP (Extended Technical Report)
In this paper we present a new approach for distributed DBMSs called P4D...
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03/26/2022
Demonstrating CAT: Synthesizing Data-Aware Conversational Agents for Transactional Databases
Databases for OLTP are often the backbone for applications such as hotel...
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03/09/2022
ASET: Ad-hoc Structured Exploration of Text Collections [Extended Abstract]
In this paper, we propose a new system called ASET that allows users to ...
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03/08/2022
It's AI Match: A Two-Step Approach for Schema Matching Using Embeddings
Since data is often stored in different sources, it needs to be integrat...
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01/03/2022
Zero-Shot Cost Models for Out-of-the-box Learned Cost Prediction
In this paper, we introduce zero-shot cost models which enable learned c...
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05/26/2021
ReStore – Neural Data Completion for Relational Databases
Classical approaches for OLAP assume that the data of all tables is comp...
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05/03/2021
One Model to Rule them All: Towards Zero-Shot Learning for Databases
In this paper, we present our vision of so called zero-shot learning for...
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09/20/2020
On the Throughput Optimization in Large-Scale Batch-Processing Systems
We analyze a data-processing system with n clients producing jobs which ...
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09/04/2020
AnyDB: An Architecture-less DBMS for Any Workload
In this paper, we propose a radical new approach for scale-out distribut...
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09/11/2019
DBPal: Weak Supervision for Learning a Natural Language Interface to Databases
This paper describes DBPal, a new system to translate natural language u...
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09/02/2019
DeepDB: Learn from Data, not from Queries!
The typical approach for learned DBMS components is to capture the behav...
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04/02/2019
Learning a Partitioning Advisor with Deep Reinforcement Learning
Commercial data analytics products such as Microsoft Azure SQL Data Ware...
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12/19/2018
Progressive Data Science: Potential and Challenges
Data science requires time-consuming iterative manual activities. In par...
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11/29/2018
Chiller: Contention-centric Transaction Execution and Data Partitioning for Fast Networks
Distributed transactions on high-overhead TCP/IP-based networks were con...
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11/15/2018
Model-based Approximate Query Processing
Interactive visualizations are arguably the most important tool to explo...
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04/07/2018
IDEBench: A Benchmark for Interactive Data Exploration
Existing benchmarks for analytical database systems such as TPC-DS and T...
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04/02/2018
An End-to-end Neural Natural Language Interface for Databases
The ability to extract insights from new data sets is critical for decis...
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01/30/2018