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Building Efficient Query Engines using High-Level Languages

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Fast query and transaction processing is the goal of 40 years of database research and the reason of existence for many new database system architectures. In data management, system performance means acceptable response time and throughput on critical-path ...

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We present the design and implementation of a SQL query processor that outperforms existing database systems and is written in just about 500 lines of Scala code – a convincing case study that high-level functional programming can handily beat C for system ...

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Query plans offer diverse tradeoffs between conflicting cost metrics such as execution time, energy consumption, or execution fees in a multi-objective scenario. It is convenient for users to choose the desired cost tradeoff in an interactive process, dyna ...

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In this paper we advocate that it is time for a radical rethinking of database systems design. Developers should be able to leverage high-level programming languages without having to pay a price in efficiency. To realize our vision of abstraction without ...

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Over the past 40 years, hard disks, the traditional building block of storage systems, have become increasingly slower when compared to the other system components such as the main memory and the CPU. Hard disks face mechanical constraints that cause their ...

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The common "one size does not fit all" paradigm isolates transactional and analytical workloads into separate, specialized database systems. Operational data is periodically replicated to a data warehouse for analytics. Competitiveness of enterprises today ...

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Modern state-of-the-art database systems are designed around a single data storage layout. This is a fixed decision that drives the whole architectural design of a database system, i.e., row-stores, column-stores. However, none of those choices is a univer ...

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