B-trees have high branching factor, so they stay shallow and reduce disk IO (fewer page reads). BSTs are pointer-heavy and deep; they are good in memory but inefficient on disk compared to page-friendly B-trees.
Advanced answer
Deep dive
Expanding on the short answer — what usually matters in practice:
Context (tags): b-tree, bst, disk-io, indexes
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-binary-search-tree-—-why-are-b-trees-c"
function explain() {
// Start from the core idea:
// B-trees have high branching factor, so they stay shallow and reduce disk IO (fewer page re
}
Common pitfalls
Too generic: no concrete trade-offs or examples.
Mixing average-case and worst-case (e.g., complexity).