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.

翻译：数据湖在大数据管理和数据分析领域日益普及。与传统数据仓库等“写时模式”方法不同，数据湖是以原始格式存储原始数据并提供统一访问接口的存储库。尽管学术界和工业界对此产生了浓厚兴趣，但数据湖的定义、功能和可用技术仍存在大量模糊之处。目前仍缺乏关于数据湖挑战与解决方案的完整、连贯图景。本综述回顾了数据湖的演进、架构及系统，全面概述了设计与构建数据湖所需的研究问题。我们依据数据湖提供的功能对现有方法及系统进行了分类，使本综述成为设计、实施和部署数据湖的实用技术参考。希望本文对现有解决方案的深入比较及对开放研究挑战的探讨，能够推动数据湖研究与实践的进一步发展。