Metadata Systems for Data Lakes: Models and Features
Databases
2019-09-23 v1
Abstract
Over the past decade, the data lake concept has emerged as an alternative to data warehouses for storing and analyzing big data. A data lake allows storing data without any predefined schema. Therefore, data querying and analysis depend on a metadata system that must be efficient and comprehensive. However, metadata management in data lakes remains a current issue and the criteria for evaluating its effectiveness are more or less nonexistent.In this paper, we introduce MEDAL, a generic, graph-based model for metadata management in data lakes. We also propose evaluation criteria for data lake metadata systems through a list of expected features. Eventually, we show that our approach is more comprehensive than existing metadata systems.
Cite
@article{arxiv.1909.09377,
title = {Metadata Systems for Data Lakes: Models and Features},
author = {Pegdwendé Sawadogo and Etienne Scholly and Cécile Favre and Eric Ferey and Sabine Loudcher and Jérôme Darmont},
journal= {arXiv preprint arXiv:1909.09377},
year = {2019}
}