DocumentDB
MongoDB-compatible document database.
Problem it solves: Aggregates read and written as a whole.
Where it sits: Behind services.
When to use
- Self-contained aggregates with evolving schema.
When not to use
- Heavily relational data with joins.
Failure modes
- Unbounded document growth.
- Cross-document consistency gaps.
Metrics to watch
- Ops/s
- Index size
Alternatives
- Relational
Configuration in Labs (illustrative defaults)
- Capacity per instance (req/s) = 8000 — Maximum requests one instance completes per second before it saturates.
- Write capacity (primary) (writes/s) = 4000 — Writes the single primary can absorb per shard. Replicas do not add write capacity.
- Read replicas (count) = 2 — Each replica adds one instance of read capacity. Replication lag is not modelled numerically.
- Shards (count) = 1 — Partitions; each multiplies read and write capacity assuming keys spread evenly (no hot key).
- Base service time (ms) = 4 — Processing time per request at zero load. Queueing adds to this as utilisation rises.
Vendor examples (pattern only): AWS managed service. Simulated as a generic “Document store”.