Choose PostgreSQL when...

• •Your application requires complex queries with JOINs across multiple tables, aggregations, window functions, or full-text search that SQL handles naturally.
• •You need ACID transactions spanning multiple entities, such as financial operations that must atomically update accounts, ledger entries, and audit logs.
• •Your access patterns are unpredictable or evolving, and you need the flexibility to create ad-hoc queries, add indexes dynamically, and run analytical queries.
• •You want a rich extension ecosystem: PostGIS for geospatial, pg_vector for embeddings, TimescaleDB for time series, pg_cron for scheduling.
• •Data integrity enforcement at the database level (foreign keys, constraints, triggers, unique indexes) is important for your domain.

Choose DynamoDB when...

• •Your access patterns are well-defined at design time and primarily consist of key-value lookups and range queries on a sort key.
• •You need predictable single-digit millisecond latency at any data scale, from gigabytes to petabytes, without performance degradation.
• •Operational simplicity is a priority: you want a fully managed database with no servers, backups, vacuuming, or connection pooling to manage.
• •Your workload has highly variable traffic patterns and you want to use on-demand capacity to automatically scale from zero to thousands of requests per second.
• •You are building on AWS and want deep integration with Lambda, API Gateway, Step Functions, and other serverless services through DynamoDB Streams and event triggers.

Is DynamoDB faster than PostgreSQL?

For primary key lookups and range queries, DynamoDB provides consistent single-digit millisecond latency regardless of table size, which PostgreSQL cannot guarantee for very large tables. However, PostgreSQL can be faster for complex queries (JOINs, aggregations) because it executes them in a single database call, while DynamoDB would require multiple queries and application-level processing.

Can I use PostgreSQL at massive scale?

Yes, but it requires significant effort. Strategies include read replicas (pgpool-II, PgBouncer), partitioning (native table partitioning), Citus for distributed PostgreSQL, and application-level sharding. Managed services like Amazon RDS and Aurora simplify scaling. However, these approaches add operational complexity that DynamoDB avoids through automatic partitioning.

What is DynamoDB single-table design?

Single-table design is a data modeling approach where multiple entity types are stored in one DynamoDB table using carefully crafted partition and sort keys. For example, users, orders, and products might share a table with composite keys like PK=USER#123 SK=ORDER#456. This enables efficient access patterns without JOINs but requires upfront access pattern analysis and makes ad-hoc queries difficult.

How does pricing compare?

PostgreSQL (on RDS) charges per instance hour plus storage, making costs predictable. DynamoDB in on-demand mode charges per read/write request unit, which is cost-effective at low throughput but expensive at sustained high volume. DynamoDB provisioned mode offers lower per-request costs but requires capacity planning. At very high throughput, PostgreSQL on appropriately sized instances is typically cheaper.

Can I migrate from PostgreSQL to DynamoDB?

Migration is possible but non-trivial because the data models are fundamentally different. You must redesign your schema from normalized relational tables to DynamoDB's key-value model, rewrite queries as key-value lookups, handle data denormalization, and rethink transactions. AWS DMS (Database Migration Service) can help with data transfer, but the schema redesign and application changes require significant engineering effort.