The Tool Desk
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What does a database index do?
An index stores searchable key information that can help the database locate candidate rows or documents more directly than examining every record. Whether it helps depends on the query, the data, and the index design; having an index does not guarantee that every query will run faster.
Database engines offer different index types and features. PostgreSQL documents B-tree, hash, GiST, SP-GiST, GIN, and BRIN indexes, as well as multicolumn, partial, and covering indexes. The right choice depends on the query and workload, not just the table’s existence. PostgreSQL’s index documentation describes these options.
Do indexes slow down writes?
They can. When data changes, the engine may have to maintain the relevant index entries as well as the underlying row or document. The cost depends on which indexed fields change and on how the database handles that operation, so index count alone does not tell you the cost of a particular write.
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- Inserts: The database generally needs to add relevant keys to the applicable indexes.
- Deletes: It generally needs to remove the corresponding keys.
- Updates: The engine may need to update indexes containing fields that changed; an update need not affect every index.
MongoDB 8.0 explains that each collection index adds write overhead and that updates may affect only a subset of indexes. Microsoft’s SQL Server design guide also notes that changes to indexed columns can require index updates. See MongoDB’s write-performance guidance and the SQL Server index design guide.
How much storage do database indexes use?
Indexes consume space in addition to the underlying data, but there is no reliable universal percentage of table size to apply across engines or schemas. Size depends on factors such as the database, index type, key values, and index design.
Width matters. Adding many columns to a covering index can increase its storage footprint and the I/O and memory needed to work with it. Unnecessary indexes also consume space and can add work for the optimizer as it considers which index to use. MySQL documents these costs in its Optimization and Indexes manual; Microsoft advises keeping indexes narrow in its design guide.
How do I know which indexes to keep or remove?
Review indexes against real query plans and workload evidence before adding or dropping one. Look for the queries an index is meant to support, whether those queries matter to the application, and whether usage information shows the index is helping. An index that is not used by the workload under review may still impose storage and write costs.
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- Identify the query: Use the engine’s query-plan tools to understand which queries are slow or important and how they access data.
- Check index use: Consult the engine’s index-usage information and verify that the candidate index is serving relevant queries. PostgreSQL documents index-usage examination, while MongoDB recommends checking whether existing indexes are actually used.
- Account for writes: Consider how often rows change and whether the changed fields appear in the index.
- Compare the footprint: Evaluate index width, storage, and resource costs alongside the query benefit.
- Validate changes: Test proposed additions or removals against the actual workload and observe both read and write behavior.
There is no universal index-removal list or maintenance interval that applies across database products. The relevant usage evidence and available tools differ by engine and version. See PostgreSQL’s index chapter and MongoDB’s write-performance guidance.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What should I compare before adding an index?
| Decision factor | What to examine |
|---|---|
| Query benefit | Which actual queries the index supports, their importance, and whether plans show it is used. |
| Write impact | How frequently data changes and which indexed fields those writes affect. |
| Index footprint | Index type and width, plus storage, I/O, and memory implications. |
| Evidence of use | Whether usage information shows the index serving important queries; interpret observations in the context of the workload measured. |
| Operational impact | How creating, rebuilding, or changing the index affects production operations on the specific engine and version. |
SQL Server advises restraint with indexes on heavily modified tables and recommends narrow indexes. Those recommendations describe SQL Server design guidance; other engines may have different implementation details.
Can creating an index affect a live database?
Yes. Index creation can affect production operations, and the exact behavior depends on the engine, version, and command. PostgreSQL’s version 17 documentation distinguishes its ordinary build from a concurrent build:
- Ordinary build:
CREATE INDEXblocks writes to the relation until the build completes. - Concurrent build:
CREATE INDEX CONCURRENTLYallows normal operations to continue, but performs two scans and takes significantly longer.
These are PostgreSQL 17 behaviors, not general rules for other databases or PostgreSQL versions. Check the documentation for the engine and version in use before choosing a production procedure: PostgreSQL 17 CREATE INDEX.
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