Database / CouchDB Interview Questions
How does CouchDB compare to MongoDB for document storage use cases?
Both CouchDB and MongoDB are JSON document databases, but they make fundamentally different architectural choices that determine where each excels.
| Aspect | CouchDB | MongoDB |
|---|---|---|
| Query interface | HTTP REST — any HTTP client; Mango JSON queries | MongoDB wire protocol; requires language driver |
| Query power | Mango (limited) + MapReduce; no aggregation pipeline | Rich aggregation pipeline; $lookup (join); text search; geospatial |
| Replication / sync | First-class HTTP peer-to-peer; PouchDB offline-first | Replica sets; change streams; no offline-first protocol |
| Conflict handling | Multi-master conflicts surfaced and resolved by app | Replica set — single primary; no write conflicts by design |
| Transactions | ACID per document; no multi-document transactions | ACID multi-document, multi-collection transactions (4.0+) |
| Write throughput | Lower — fsync per write; append-only B-tree | Higher — WiredTiger storage with group commit |
| Mobile / offline sync | Excellent — PouchDB is production-grade | Atlas Device Sync (commercial); no free equivalent |
| Deployment simplicity | Single binary, zero dependencies | More complex; requires mongod + replica set for production HA |
Choose CouchDB when the offline-first / mobile sync use case is central, when HTTP-native access matters (IoT, edge devices, no-driver environments), or when you need a simple embedded-friendly document store. Choose MongoDB when you need a rich aggregation pipeline, multi-document ACID transactions, geospatial queries, or high write throughput at scale.
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