There are no fixed limitations on data lake storage. What is a data lake?Ī data lake is a large repository that stores huge amounts of raw data in its original format until you need to use it. There are fundamental differences between lakes and warehouses, including: Both solutions store a much larger amount of data than a database and both also support overall data mangement - but that’s about where the similarities end. There can still be a lot of data (and information) stored in a database, but nothing on the scale of big data storage solutions.Įnter data lakes and data warehouses. A database is a collection of structured data and is best utilized for storing and analyzing relatively small data sets. And we'll touch briefly on other storage, like data lakehouses, databases and data marts.ĭata lake, data warehouse… database? Data lakehouse?īefore we dive into the topic of a data lakes and warehouses, it’s important to note that neither is classed as a database.Data lakes are immense and could contain…all sorts of data, raw, unstructure - whatever!.Data warehouses are organized and more immediately useful to business needs, though with certain limitations.The general rule of thumb is in their names: We’ll examine the benefits of each, then discuss the key differences between a data lake and a data warehouse, so you can decide on the best approach for your business. This article explores two primary types of big data storage: data lakes and data warehouses. Storing this data is important - but deciding on the right type of data storage solution is not so clear. There is more data available to us than ever.

Data warehouse vs data lakehouse