Tutorials System Design Tutorial
Database Indexing at Scale — Complete Guide
Database Indexing at Scale — Complete Guide: free step-by-step lesson with examples, common mistakes, and interview tips — part of System Design Tutorial on Toolliyo Academy.
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System Design Tutorial · Lesson 26 of 100
Database Indexing at Scale
Basics → Scale → Interview
Basics · 1 — Building blocks · ~6 min · Module 3: Database Systems
What is this?
Indexes speed lookups and sorts by maintaining extra structures (B-trees, etc.) — at the cost of write overhead and storage.
Why should you care?
ShopNest “orders by user” must not scan millions of rows on every profile open.
See it live — copy this example
Sketch the architecture on paper. These lessons focus on concepts and trade-offs.
Orders
PK (orderId)
INDEX (userId, createdAt DESC) -- history page
INDEX (status) WHERE status='OPEN' -- ops queue (filtered)
Write path updates indexes too — measure insert costRun Example »
This lesson uses terminal or setup steps. Run commands on your computer — the live editor appears on coding lessons.
What happened?
- Composite order matches the query.
- Filtered indexes help sparse statuses.
- Too many indexes slow checkout writes.
Practice next
- Add (userId, createdAt) for history.
- Explain why status-alone may be weak if mostly OPEN.
- Review unused indexes quarterly.
- Cover a query with INCLUDE columns (SQL Server) or similar.
- Drop an index unused for 30 days in staging.
Remember
Indexes match real WHERE/ORDER BY. Writes pay for each index. Measure with plans.
User order history index
ShopNest adds (userId, createdAt) on Orders.
Outcome: Profile history p95 drops from seconds to milliseconds.
Interview prep for this lesson
Practice these questions aloud after reading—each links to a full structured answer.
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