For a high-throughput, low-latency application, which database option best supports scale and performance?

• A. DynamoDB for highly scalable, low-latency workloads; use Aurora for relational data if needed
• B. RDS MySQL
• C. Redshift
• D. Neptune

Answer: (A)

For high-throughput, low-latency applications, you want a database that can scale out seamlessly while delivering fast, predictable responses. DynamoDB fits this need because it is a fully managed NoSQL database that automatically partitions data to scale with demand, providing single-digit millisecond latency at any scale. You can choose on-demand capacity for sudden traffic spikes or provisioned throughput with auto-scaling, ensuring performance remains stable as load grows. For many real-time use cases—such as shopping carts, session stores, gaming, or telemetry—this combination of elastic scalability and low latency is exactly what’s required.

Relational databases like RDS MySQL can scale, but they often require more careful planning and may not match DynamoDB’s latency at very high throughputs. Redshift is optimized for analytical queries on large datasets, not for low-latency transactional workloads. Neptune focuses on graph workloads, which have different access patterns and performance needs.