Skip to contentScholarGate
LibraryBookshelfDeskReview StudioAssistant
Sign in
On this page
IntuitionHow it worksWhen to use itStrengths & limitationsCommon pitfallsApplicationsFrequently asked🔒 Read the full methodSourcesRelated methods
Cite this pageSpotted an issue on this page? Report or suggest a fix →
Home›Information Systems›Indexing Strategy
Process / pipelineQuery Processing & Performance

Indexing Strategy

Database Indexing Strategy and Design · Also known as: index design, indexing

Indexing strategy is the practice of systematically designing database indexes to accelerate query performance. Developed following Bayer and McCreight's foundational B-tree work in 1972, effective indexing requires analyzing query patterns, choosing appropriate index structures, and maintaining index health as data evolves.

ScholarGate
  1. Process / pipeline
  2. v1
  3. 3 Sources
  4. PUBLISHED
Cite this page →
Tools & resources
Download slides
Learn & explore

Read the full method

Members only

Sign in with a free account to read this section.

Sign in

Method map

The neighbourhood of related methods — select a node to explore.

Indexing Strategy
Query Optimization

When to use it

Use indexing strategy whenever query response time is unacceptable or resources are over-utilized. It is most effective for columns used in WHERE, JOIN, and ORDER BY clauses, and for tables with selective queries. Assumptions include that update performance trade-offs are acceptable and that statistics are current.

Strengths & limitations

Strengths
  • Can reduce query execution time from seconds to milliseconds for selective predicates
  • Applies to existing applications without code modification
  • Adapts to changing query patterns through index redesign and addition
Limitations
  • Indexes consume storage and slow down INSERT, UPDATE, and DELETE operations
  • Index maintenance overhead can become significant for high-write workloads
  • Poorly chosen indexes provide no benefit and waste resources

Frequently asked

Should I index every column used in a WHERE clause?

No. Prioritize columns with high selectivity (that eliminate many rows) and columns used frequently. Low-selectivity columns (e.g., gender with 2 values) provide minimal benefit. Use composite indexes for multiple frequently-used columns.

What is a composite index and when should I use it?

A composite index includes multiple columns in a specific order. Use when queries frequently filter or sort by multiple columns together. Example: INDEX(customer_id, order_date) helps queries that filter by customer AND order date.

How do I know if an index is being used?

Use EXPLAIN or EXPLAIN PLAN to show the query execution plan. If the plan shows an index name and Index Scan/Seek operations, the index is being used. If it shows Table Scan, the index is not being used.

What is index fragmentation and why does it matter?

Fragmentation occurs when index pages are not stored contiguously on disk, requiring more I/O operations. Defragmentation (REBUILD or REORGANIZE) restores contiguity and improves performance, especially for range queries.

Sources

  1. Bayer, R., & McCreight, E. (1972). Organization and maintenance of large ordered indices. Acta Informatica, 1(3), 173-189. DOI: 10.1007/BF00288683 ↗
  2. Seltzer, M., & Bostic, K. (1994). An implementation of a log-structured file system for UNIX. Winter USENIX Conference, 307-326. link ↗
  3. Garcia-Molina, H., Ullman, J. D., & Widom, J. (2009). Database Systems: The Complete Book (2nd ed.). Pearson Education. link ↗

How to cite this page

ScholarGate. (2026, June 3). Database Indexing Strategy and Design. ScholarGate. https://scholargate.app/en/information-systems/indexing-strategy

Related methods

Query Optimization

Which method?

Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.

  • Query OptimizationInformation Systems↔ compare
Compare side by side →

Referenced by

Query Optimization

Similar methods

Query OptimizationDatabase PartitioningNoSQL Schema DesignDatabase NormalizationOLAP Cube DesignData WarehousingTransaction ManagementConcurrency Control

Related reference concepts

Indexing and Access MethodsQuery Processing and OptimizationCost-Based Query OptimizationJoin AlgorithmsSearch TreesDatabase Design and Normalization

Spotted an issue on this page? Report or suggest a fix →

ScholarGate — Indexing Strategy (Database Indexing Strategy and Design). Retrieved 2026-07-21 from https://scholargate.app/en/information-systems/indexing-strategy · Dataset: https://doi.org/10.5281/zenodo.20539026
Quick facts
Originator
Rudolf Bayer and Edward M. McCreight
Subfamily
Query Processing & Performance
Year
1972
Type
Database optimization technique
Related methods
Query Optimization
ScholarGate

A content-first reference library for research methods — what each one is, how it works, and where it comes from.

Open data (CC-BY)

Explore

  • Library
  • Search the library…
  • Browse by field
  • Fields
  • Journey
  • Compare
  • Which method?

Reference

  • Subjects
  • Atlas
  • Glossary
  • Methodology
  • Philosophy

Your tools

  • Bookshelf
  • Desk
  • Chat

Company

  • About
  • Pricing
  • Contact
  • Suggest a method

Entries are compiled from published sources for reference. Verifying the accuracy and suitability of any information for your own use remains your responsibility.

© 2026 ScholarGate · A research-method reference library
  • Privacy
  • Cookies
  • Terms
  • Delete account