With the arrival of the European Union's General Data Protection Regulation (GDPR),
several companies are making significant changes to their systems to achieve compliance …

Scanning and filtering are the foundations of analytical database systems. Modern DBMSs
employ a variety of techniques to partition and layout data to improve the performance of …

Shared-nothing, distributed databases scale transactional and analytical processing over a
large data volume by spreading data across servers. However, static sharding of data across …

Introducing new (learned) features into a DBMS requires considerable experimentation and
benchmarking to avoid regressions in production (customer) workloads. Using standard …

The twenty-first century has been dominated by the need for large scale data processing,
marking the birth of big data platforms such as Cosmos. This paper describes the evolution …

We study the problem of optimizing data storage and access costs on the cloud while
ensuring that the desired performance or latency is unaffected. We first propose an optimizer …

Index tuning is crucial for database performance, but existing algorithms are often tailored
for single instances, posing challenges in cluster architectures. While uniform tuning …

As data are processed by diverse clients ranging from urgent time-critical to best-effort,
supporting different QoS (Quality of Service) becomes a vital component in a distributed …

In this paper, we initiate a theoretical study of what we call the join covering problem. We are
given a natural join query instance $ Q $ on $ n $ attributes and $ m $ relations $(R_i) _ {i\in …

The twenty-first century has been dominated by the need for large scale data processing,
marking the birth of big data platforms such as Cosmos. This paper describes the evolution …