At a time when the complexity and popularity of data-driven applications are growing at an unprecedented rate, INESC TEC and Carnegie Mellon University (CMU) are collaborating on a project to tackle one of the most debated challenges in the field: the efficiency of the data-processing systems that support these applications. The project, called ADAPQO, aims to transform the way databases make decisions.
In modern database systems, the optimiser is the component responsible for determining the best way to execute each user query. Faced with millions of potential alternatives, this decision has become increasingly difficult, with a direct impact on performance and system efficiency – especially in a context where the diversity of databases is expanding to meet the needs of new Artificial Intelligence (AI) applications.
To address this challenge, ADAPQO aims to develop a new type of optimiser capable of learning from experience and continuously improving decision-making capabilities. “The vision is to create an autonomous service that collects knowledge over time and can be easily integrated into different data management systems,” said José Orlando Pereira. “Beyond the technological impact, the initiative is also expected to accelerate research and boost advanced training in the field of databases,” added the researcher, who is also a professor at the University of Minho.
Building on an already well-established research line at INESC TEC, the Institute is represented by José Orlando Pereira, Ana Nunes Alonso and Nuno Faria, INESC TEC researchers in databases, who coordinate the Portuguese component of the project and participate actively in the scientific and technological development. Concerning the U.S.A., the project involves the collaboration of Andy Pavlo, leader of the CMU Database Group and an international reference in the field.
The researchers mentioned in this news piece are associated with INESC TEC and UMinho.
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