One essential data mining component is selecting an efficient data storage and extraction solution. This chapter introduces databases as structured, electronic collections of data manipulated via database management systems (DBMS), emphasizing their role in enabling secure storage, retrieval, and analysis. Key concepts like structured query language (SQL) and relational database systems are discussed, highlighting their strengths in handling structured data like tables. The chapter also examines alternative storage options, including on-premises, cloud, and hybrid systems, along with their advantages and challenges, such as scalability and data security. Topics like CRUD operations, database joins, and data aggregation are discussed and supported by examples. Finally, the chapter provides hands-on Python exercises for combining datasets and analyzing relationships, fostering database and data mining integration skills. The exercise uses data from climate change discussions on social media, classified into messages sent by those concerned about climate change (“activists”) and those who expressed a denial or skepticism (“skeptics”).