Chapter 2. Managing Data with Delta Lake
Data lakehouses leverage specialized storage frameworks to enhance the functionality of traditional data lakes. Among these frameworks, Delta Lake stands out as a leading technology that powers the Databricks Lakehouse Platform. In this chapter, we’ll explore the fundamental concepts of Delta Lake by first introducing its core principles and then diving into its practical usage. Following this, we’ll focus on advanced topics in Delta Lake such as time travel, table optimization, and vacuum operations.
Introducing Delta Lake
Traditional data lakes often suffer from inefficiencies and encounter various challenges in processing big data. Delta Lake technology is an innovative solution designed to operate on top of data lakes to overcome these issues. To establish a clear understanding of Delta Lake, let’s first study its definition as provided by its original creators at Databricks.
What Is Delta Lake?
Delta Lake is an open-source storage layer that brings reliability to data lakes by adding a transactional storage layer on top of data stored in cloud storage.
Databricks
In the context of data lakehouses, a storage layer refers to the framework responsible for managing and organizing data stored within the data lake. It serves as an intermediary platform through which data is ingested, queried, and processed.
In other words, Delta Lake is not a storage medium or storage format. Common storage formats like Parquet or JSON define how data ...
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