What methods can be used to increase the performance of relational databases as data volume grows?

To improve the performance of relational databases as data volume grows, the following methods can be used:

• Indexing — creating indexes on frequently used columns to speed up searches.
• Sharding — dividing the database into parts (shards) to distribute the load.
• Caching — storing frequently requested data in memory for quick access.
• Query optimization — rewriting queries to reduce execution costs.
• Vertical and horizontal scaling — increasing server resources or adding new servers.
• Using table partitioning — dividing large tables into smaller parts based on a key.

For example, in Python, you can use an ORM with support for lazy loading and caching to reduce the number of database queries.