Document Database — Notes

Functional

• Schema-flexible JSON / BSON documents.
• Rich query language with secondary indexes.
• Sharding + replication built-in.
• Aggregation pipelines.
• Multi-document transactions.

Non-functional

• 10–50k ops/s/shard (varies with workload).
• Replica set HA: failover seconds.
• Linearizable reads on request (read concern majority + linearizable).

Capacity

• Per shard: 1–4 TB working set; up to 64 TB+ disk.
• Cluster sizes routinely 10–100 shards.

API

• Drivers (Mongo, Couchbase) speak native protocol; OpQuery / OP_MSG.
• HTTP layer via Atlas Data API or REST gateways.

Schema (conceptual)

• db.collection holds documents {_id, ...}.
• Shard key chosen at create time, hard to change.

Trade-offs

• Flexible schema = velocity at start, debt over time. Add JSON schema validators.
• Embedded vs referenced docs: embed for 1-to-few; reference for many-to-many.
• Sharded transactions are real but slow; design hot paths to stay single-shard.
• Eventually consistent secondary reads vs majority reads: pick per query.

Refs

• MongoDB docs (sharding, replication, oplog, change streams).
• "Designing Data-Intensive Applications" doc DB chapter.
• Couchbase architecture papers; Azure Cosmos DB internals.