Query optimizer is at the heart of the database systems. Cost-based optimizer studied in this
paper is adopted in almost all current database systems. A cost-based optimizer introduces …

GPU-accelerated database systems have been studied for more than 10 years, ranging from
prototyping development to industry products serving in multiple domains of data …

Predicate pushdown is a widely adopted query optimization. Existing systems and prior work
mostly use pattern-matching rules to decide when a predicate can be pushed through …

Easy-to-use programming interfaces paired with cloud-scale processing engines have
enabled big data system users to author arbitrarily complex analytical jobs over massive …

Query rewriting is often a prerequisite for effective query optimization, particularly for poorly-
written queries. Prior work on query rewriting has relied on a set of" rules" based on syntactic …

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 …

From the recent momentum behind translating natural language to SQL (nl2sql), to
commercial product offerings such as Co-Pilot for Microsoft Fabric, Large Language Models …

Optimizing large-scale data processing has become crucial in the area of data management
due to the constantly growing quantity and complexity of data. Big data analysis involves …

Amazon Athena is a serverless, interactive query service that allows efficiently analyzing
large volumes of data stored in Amazon S3 using ANSI SQL. Some design choices in the …