Interview kitsBlog

Your dream job? Lets Git IT.
Interactive technical interview preparation platform designed for modern developers.

XGitHub

Platform

  • Categories

Resources

  • Blog
  • About the app
  • FAQ
  • Feedback

Legal

  • Privacy Policy
  • Terms of Service

© 2026 LetsGit.IT. All rights reserved.

LetsGit.IT/Categories/Data Structures
Data Structureshard

B-tree vs B+ tree: what is the practical difference and why do databases like B+ trees?

Tags
#b-tree#b-plus-tree#indexes#storage
Back to categoryPractice quiz

Answer

In a B+ tree, all records (or pointers to records) are stored in the leaves, and internal nodes store only keys for routing. Leaves are usually linked, so range scans are very fast. This fits disk access well: high fan-out keeps the tree shallow, and linked leaves make ordered reads efficient.

Advanced answer

Deep dive

Expanding on the short answer — what usually matters in practice:

  • Context (tags): b-tree, b-plus-tree, indexes, storage
  • Complexity: compare typical operations (average vs worst-case).
  • Invariants: what must always hold for correctness.
  • When the choice is wrong: production symptoms (latency, GC, cache misses).
  • Explain the "why", not just the "what" (intuition + consequences).
  • Trade-offs: what you gain/lose (time, memory, complexity, risk).
  • Edge cases: empty inputs, large inputs, invalid inputs, concurrency.

Examples

A tiny example (an explanation template):

// Example: discuss trade-offs for "b-tree-vs-b+-tree:-what-is-the-practical-differe"
function explain() {
  // Start from the core idea:
  // In a B+ tree, all records (or pointers to records) are stored in the leaves, and internal 
}

Common pitfalls

  • Too generic: no concrete trade-offs or examples.
  • Mixing average-case and worst-case (e.g., complexity).
  • Ignoring constraints: memory, concurrency, network/disk costs.

Interview follow-ups

  • When would you choose an alternative and why?
  • What production issues show up and how do you diagnose them?

Related questions

Data Structures
B-tree vs binary search tree — why are B-trees common on disk?
#b-tree#bst#disk-io
MongoDB
Unique vs sparse vs partial indexes: what’s the difference?
#mongo#indexes#unique
MongoDB
Capped collections: what are they and when are they useful?
#mongo#capped-collection
  • How would you test edge cases?
  • #storage
    PostgreSQL
    BRIN index: when is it useful?
    #postgres#brin#indexes
    PostgreSQL
    GIN vs GiST indexes: when would you use each?
    #postgres#indexes#gin
    Databases
    What is a covering index (index‑only scan) and why can it be faster?
    #database#indexes#covering-index