Now that we have discussed some of the essential elements of a data lake in the context of Lambda Architecture, it is imperative that the complete story around data lake starts from capturing the data from source systems, which we are referring to as Data Acquisition.

Data can be acquired from various systems, in which data may exist in various forms. Each of these data formats would need a specific way of data handling such that the data can be acquired from the source system and put to action within the boundaries of data lake.

In this chapter, we would be specifically looking at acquiring data from relational data sources, such as a Relational DataBase Management System (RDBMS) and discuss specific patterns for the same. When it comes to capturing data specifically from relational data sources, Apache Sqoop is one of the primary frameworks that has been widely used as it is a part of the Hadoop ecosystem and has been very dominant for this capability.

Various technologies would now be mentioned at various points (not that you should know or we will discuss everything in this book) throughout this part of the book and the following parts as we are now in the process of actually implementing the Data Lake using various technologies.