Data Lakes

A Survey of Functions and Systems

Journal Article (2023)
Author(s)

R. Hai (TU Delft - Web Information Systems)

Christos Koutras (TU Delft - Web Information Systems)

Christoph Quix (Hochschule Niederrhein)

Matthias Jarke (Fraunhofer Institute for Applied Information Technology FIT)

Research Group
Web Information Systems
Copyright
© 2023 R. Hai, C. Koutras, Christoph Quix, Matthias Jarke
DOI related publication
https://doi.org/10.1109/TKDE.2023.3270101
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 R. Hai, C. Koutras, Christoph Quix, Matthias Jarke
Research Group
Web Information Systems
Issue number
12
Volume number
35
Pages (from-to)
12571-12590
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Abstract

Data lakes are becoming increasingly prevalent for Big Data management and data analytics. In contrast to traditional 'schema-on-write' approaches such as data warehouses, data lakes are repositories storing raw data in its original formats and providing a common access interface. Despite the strong interest raised from both academia and industry, there is a large body of ambiguity regarding the definition, functions and available technologies for data lakes. A complete, coherent picture of data lake challenges and solutions is still missing. This survey reviews the development, architectures, and systems of data lakes. We provide a comprehensive overview of research questions for designing and building data lakes. We classify the existing approaches and systems based on their provided functions for data lakes, which makes this survey a useful technical reference for designing, implementing and deploying data lakes. We hope that the thorough comparison of existing solutions and the discussion of open research challenges in this survey will motivate the future development of data lake research and practice.