Engineering high-performance database engines

Author:

Neumann Thomas1

Affiliation:

1. Technische Universität München, Munich, Germany

Abstract

Developing a database engine is both challenging and rewarding. Database engines are very complex software artifacts that have to scale to large data sizes and large hardware configurations, and developing such systems usually means choosing between different trade-offs at various points of development. This papers gives a survey over two different database engines, the disk-based SPARQL-processing engine RDF-3X, and the relational main-memory engine HyPer. It discusses the design choices that were made during development, and highlights optimization techniques that are important for both systems.

Publisher

VLDB Endowment

Subject

General Earth and Planetary Sciences,Water Science and Technology,Geography, Planning and Development

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Data dependencies for query optimization: a survey;The VLDB Journal;2021-06-14

2. To Partition, or Not to Partition, That is the Join Question in a Real System;Proceedings of the 2021 International Conference on Management of Data;2021-06-09

3. Quantifying TPC-H choke points and their optimizations;Proceedings of the VLDB Endowment;2020-04

4. Hybrid Data Layouts for Tiered HTAP Databases with Pareto-Optimal Data Placements;2018 IEEE 34th International Conference on Data Engineering (ICDE);2018-04

5. Cost-Function Complexity Matters: When Does Parallel Dynamic Programming Pay Off for Join-Order Optimization;Advances in Databases and Information Systems;2017

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