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LetsGit.IT / Categories / MongoDB Answer Replica sets provide high availability: one primary replicates to secondaries with automatic failover. Sharding provides horizontal scaling: data is partitioned across shards by a shard key and routed via mongos. You often use both together.
Advanced answer Deep dive Expanding on the short answer — what usually matters in practice:
Context (tags): replication , sharding , scalability, mongodb Data model and access patterns: dominant queries (read/write ratio, sorting, pagination). Indexes: when they help vs hurt (write amplification, memory). Consistency & transactions: what’s guaranteed and what can bite you. 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 (query + projection):
// Example: query + projection
const user = await db.collection('users').findOne(
{ email: '[email protected] ' },
{ projection: { _id: 0, email: 1, name: 1 } },
)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?
How would you test edge cases? #mongodb