dynamodb

To design a DynamoDB schema for multiple access patterns, identify all required query patterns first, then structure partition and sort keys to satisfy them efficiently. This approach leverages single-table design and Global Secondary Indexes to support diverse workloads without full table scans.

Single-table design in DynamoDB is a modeling strategy where multiple entity types coexist in one table using generic key attributes. Use this approach to optimize query performance and reduce costs when supporting many complex access patterns across different entities within the same application.

Choose DynamoDB Global Secondary Indexes (GSIs) to query on alternate partition keys, or Local Secondary Indexes (LSIs) to query on alternate sort keys within the same partition. GSIs offer flexibility for broad lookups, while LSIs maintain strong consistency for items sharing a partition key.

Use DynamoDB on-demand capacity mode for unpredictable workloads to handle sudden spikes automatically, or provisioned capacity with auto-scaling for steady traffic to optimize costs. The best choice depends on your real-world traffic volume and predictability.

DynamoDB Local Secondary Indexes (LSIs) are limited to 10 per table, must be created at table creation time, and only support queries against items sharing the same partition key. They also consume provisioned throughput from the base table, unlike Global Secondary Indexes.

To model multi-tenant SaaS data in DynamoDB, structure partition keys to isolate tenant data while using sort keys and Global Secondary Indexes to handle tenant-specific access patterns. This ensures secure data segregation and scalable query performance across tenants.