How can operations of reading from a constantly growing table be optimized?

To optimize read operations from a constantly growing table, several approaches can be applied:

• Indexing — creating and maintaining indexes on frequently used fields significantly speeds up queries.
• Partitioning the table — dividing the table into logical parts (by date, value range, etc.) allows reading only the necessary partitions.
• Archiving old data — moving outdated data to separate tables or databases reduces the size of the main table.
• Caching query results — using external caches (Redis, Memcached) or built-in DBMS mechanisms.
• Query optimization — analyzing and rewriting queries to minimize data scanning.
• Using materialized views — for frequently repeated complex queries.

For example, if a table contains logs for several years, it can be partitioned by months so that queries for the last month do not scan the entire table.

These methods help maintain high read performance even as data volume grows.