Basic Information
| Field | Details |
|---|---|
| English name | Amazon DynamoDB |
| Full name | Amazon DynamoDB |
| Chinese description | 无服务器 Key-Value 与文档型 NoSQL 数据库 |
| Japanese description | サーバーレス NoSQL データベース |
| Exam frequency | ⭐⭐⭐⭐⭐ |
| Often confused with | RDS / DocumentDB / DAX |
In one sentence
DynamoDB organizes tables, items, and attributes. Define access patterns first, then design partition keys, sort keys, and indexes.
Core purpose
- Partition keys distribute data; high-cardinality, even access helps avoid hot partitions.
- Query specifies a partition key and optional sort-key conditions; Scan reads broadly and normally consumes more capacity.
- Global Tables provide multi-Region multi-active access; DAX caches repeated eventually consistent reads.
Exam focus
- Serverless NoSQL, large-scale low latency, and automatic scaling point to DynamoDB.
- Shopping carts, sessions, game state, IoT, and event metadata are common use cases.
- Choose consistency, capacity mode, indexes, TTL, Streams, and backups from access patterns.
Common misconceptions
- NoSQL does not mean no schema; primary-key structure still matters.
- DynamoDB is not designed for arbitrary joins or ad hoc relational queries.
Key takeaway
Table → item → attribute; define access patterns before partition keys; prefer Query to Scan.
Related services
DAX, Lambda, API Gateway, Streams, Global Tables, AWS Backup.