Chapter 3: Reading Time Series Data from Databases

Databases extend what you can store to include text, images, and media files and are designed for efficient read and write operations at a massive scale. Databases can store terabytes and petabytes of data with efficient and optimized data retrieval capabilities, such as when we are performing analytical operations on data warehouses and data lakes. A data warehouse is a database designed to store large amounts of structured data, mostly integrated from multiple source systems, built specifically to support business intelligence reporting, dashboards, and advanced analytics. A data lake, on the other hand, stores a large amount of data that is structured, semi-structured, or unstructured in its raw format. In this chapter, we will continue to use the pandas library to read data from databases. We will create time series DataFrames by reading data from relational (SQL) databases and non-relational (NoSQL) databases.

Additionally...