Symbolic sequence databases are widely used in fields such as bioinformatics, where analyzing DNA, RNA, and protein sequences is critical for understanding diseases and developing new drugs. This chapter presents an overview of symbolic sequence databases, focusing on their mathematical, practical representations and methods for generating and analyzing synthetic sequence data. We also explore techniques for discovering frequent contiguous patterns in symbolic sequences, essential for uncovering hidden relationships and insights within large datasets. The chapter introduces the PAMI library, which implements powerful tools such as the PositionMining algorithm for mining frequent contiguous patterns. These tools, along with database statistics and synthetic data generation capabilities, provide a comprehensive framework for researchers to analyze and extract meaningful patterns from symbolic sequence data.