Indexes can dramatically improve query performance — but only when they’re used wisely. Adding indexes to the wrong columns can slow down writes, inflate storage, and even make queries worse. So how do you know which columns deserve an index?
Let’s break it down.
Good Candidates for Indexing
These types of columns are typically strong choices for indexes:
1. Columns Frequently Used in WHERE Clauses
If a column appears often in filters, it’s a prime candidate.
Examples:
-
WHERE status = 'ACTIVE' -
WHERE customerId = 123
The more selective the column (i.e., it filters down many rows to a few), the more effective the index will be.
2. Columns Used in JOIN Conditions
Indexes on join keys help databases match rows faster across tables.
Examples:
-
user.id = order.userId -
product.id = orderItem.productId
Foreign key columns are especially good candidates.
3. Columns Used in ORDER BY or GROUP BY
Indexes can help avoid sorting work if the index already stores rows in the required order.
Examples:
-
ORDER BY createdDate -
GROUP BY country
This is particularly valuable on large tables.
4. Columns Used in High-Read / Low-Write Workloads
Indexes shine in analytical or reporting queries where reads dominate writes.
Examples:
-
dashboards
-
reports
-
search screens
Bad Candidates for Indexing
Not every column benefits from indexing — some can actually harm performance.
1. Columns with Very Low Selectivity
If most rows have the same value, an index adds overhead without improving query performance.
Examples:
-
boolean flags (
isActive) -
“status” columns with only a few values
-
gender fields
The database will still scan many rows.
2. Columns That Change Frequently
Every write must update every index — meaning volatile columns can slow inserts/updates.
Avoid indexing:
-
counters
-
frequently updated timestamps
-
log/event values
3. Very Small Tables
Indexes don’t help when the entire table fits in memory — a full scan is often faster.
If there are only a few hundred rows, skip the index.
4. Columns Not Used in Queries
If a column never appears in WHERE/JOIN/GROUP/ORDER — it doesn’t need an index. Simple rule.
What to Watch Out For
Before adding an index, consider these trade-offs:
Indexes Speed Reads — But Slow Writes
Every insert, update, and delete must maintain the index structure. Too many indexes = laggy writes.
Composite Indexes Require Careful Ordering
An index on (firstName, lastName) is not the same as (lastName, firstName).
Create them in the order queries actually use.
Over-Indexing Wastes Memory & Storage
Indexes consume space — sometimes more than the table itself.
Audit unused indexes periodically.
Use EXPLAIN / Query Plans
Always validate assumptions. Let the database show you whether an index is being used or ignored.
Summary
Indexes are powerful — but they aren’t “free.”
Index columns that are:
-
frequently filtered in WHERE clauses
-
used in JOINs
-
part of ORDER BY / GROUP BY
-
selective and relatively stable
Avoid indexing columns that:
-
have low selectivity
-
change frequently
-
belong to very small tables
-
aren’t used in queries
When in doubt: measure first, index second.
