Database research at HASLab is motivated by the key role played by database systems in modern society, triggering a lot of interest from research to industry such as cloud computing, internet-of-things, storage formats for data processing or machine learning/artificial intelligence.

The core team has a strong background in fault-tolerant agreement and group communication protocols and several years ago started applying them on the research and implementation of advanced database replication based on group communication.

With the rise of massive applications such as social networking platforms, the team research focus on a new generation of elastic data management solutions, that can scale both in the sheer volume of data that can be held but also in how required resources can be dynamically and incrementally provisioned. This includes both work on elastic data management for cloud computing environments from high-throughput online querying to elastic workload aware tuple store management; novel strategies for parallel SQL query language engine and parallel execution of window functions; research on data lakes support in SQL query engines to use data from external stores.

Despite its many benefits, cloud solutions have been designed without strong data confidentiality guarantees. To overcome the lack of privacy guarantees in the cloud, the team is working on a new area, secure data processing, that aims at building practical database systems that follow a privacy-by-design methodology.

By covering a large spectrum of nowadays Database research, we intend to contribute to the next generation of secure, distributed, scalable and fault-tolerant database systems that are able to seamlessly adapt to heterogeneous hardware configurations powered by current cloud computing infraestructures and able to adapt to sheer volume of data handled today and the expected increase in years to come (for more details please see Research).