Data Indexing

A practical example

Example: a sales dashboard filters opportunities by owner and stage. Without indexes, every refresh scans the full table and times out.

After indexing those two columns, the same filter reads only matching rows and returns in seconds.

What to evaluate before investing

• Ask which columns are indexed by default and whether you can add indexes yourself.
• Check whether indexes slow down ingestion or sync writes in your vendor's implementation.
• Confirm the engine maintains index statistics so the planner actually uses them.

Limitations and tradeoffs

Tradeoff: every index speeds reads but adds storage and write overhead. Indexing every filterable column degrades ingestion performance, so teams must index the few columns their dashboards and lookups actually hit.