The text discusses the importance of building the right indexes for time-series data in a database like TimescaleDB, which is built on PostgreSQL. The relational model allows storing relational data alongside time-series data, enabling SQL queries and joins. However, when dealing with timestamps, traditional indexes may not be sufficient, and specific considerations must be taken into account. A composite index can be effective but requires careful ordering to maximize performance. The text provides examples of different query scenarios and how the choice of index can significantly impact execution time. By using an expressive querying language like SQL, leveraging industry standards, and considering trade-offs between indexes and performance, developers can optimize their queries and improve overall database efficiency.