database

DynamoDB single-table design requires modeling all access patterns upfront by structuring partition and sort keys to support query efficiency. This involves defining key conventions and GSI configurations to ensure every query pattern is covered without table scans.

PostgreSQL schema design best practices include standardizing table naming, defining proper indexes, and writing structured migrations. Applying these conventions ensures schema changes are auditable, query performance is optimized, and connection pooling is configured correctly.

Yes, the database design guidance covers time-series data patterns and soft-delete strategies for both DynamoDB and SQL. These patterns help manage growing datasets and preserve historical records without physical deletion while maintaining query performance.

Auditing existing database schemas involves reviewing table structures, index usage, and query patterns to identify performance bottlenecks. This process applies standardized conventions to optimize both DynamoDB and PostgreSQL schemas for cost efficiency and speed.

DynamoDB single-table design becomes less suitable when access patterns are highly unpredictable or rapidly changing, as it requires extensive upfront modeling. If your application needs complex joins or ad-hoc querying, SQL or PostgreSQL schemas offer better flexibility.