Amazon Aurora vs Amazon DynamoDB

Data model and query flexibility

Aurora is a relational engine that is wire-compatible with MySQL and PostgreSQL, so it supports SQL, joins, secondary indexes, foreign keys, and ACID transactions across tables. That makes it the natural home for applications with normalized schemas, ad-hoc reporting, and evolving query patterns where you cannot predict every access path in advance.

DynamoDB is a key-value and document store where you design tables around known access patterns. Queries are fast and predictable when the partition and sort keys match the request, but there are no server-side joins and ad-hoc querying is limited. Schemas that change access patterns frequently can require table redesign or additional global secondary indexes.

Scaling and performance

DynamoDB scales horizontally and automatically by partitioning data, sustaining single-digit-millisecond latency from small tables to tables handling tens of millions of requests per second. This is its defining property: throughput is effectively unbounded without sharding logic in the application.

Aurora scales reads through up to 15 low-latency replicas and scales compute through Serverless v2 autoscaling measured in Aurora Capacity Units. Aurora separates compute from a distributed storage layer that auto-grows to 128 TiB, and Aurora Limitless Database extends write scaling through sharding. Write scaling still requires more planning than DynamoDB's automatic model.

Pricing model

Aurora bills for compute (provisioned instances or Serverless v2 ACUs), storage, and I/O, with an I/O-Optimized option that removes per-request I/O charges for I/O-heavy workloads. Serverless v2 can scale down but retains a minimum running cost, so an idle Aurora Serverless v2 database still accrues charges. Pricing verified June 2026; enterprise pricing requires a quote.

DynamoDB bills per request in on-demand mode or per provisioned capacity unit, plus storage. On-demand costs nothing when idle and dropped roughly 50 percent in late 2024, making it economical for spiky and low-traffic workloads. AWS introduced Database Savings Plans at re:Invent 2025, the first commitment discount that applies to DynamoDB on-demand. At very high sustained relational throughput, Aurora with reserved instances can be cheaper per operation.

Operations and consistency

Both are fully managed, but DynamoDB removes more operational surface: there are no instances to size, patch, or fail over. It offers eventually consistent reads by default and strongly consistent reads on request, plus global tables for multi-region. Aurora provides strong consistency within a cluster, automated backups, and fast failover, but you still choose instance classes and manage replica topology. Aurora suits teams that want relational guarantees; DynamoDB suits teams that want to minimize database operations entirely.

What buyers say

Buyers frequently note that DynamoDB delivers consistent low latency at scale and that its serverless model removes most database operations, which teams running event-driven and high-traffic systems value highly. The recurring DynamoDB criticism is that cost and design complexity grow with global secondary indexes, and that rigid access patterns punish schema changes. Aurora buyers frequently praise its drop-in MySQL and PostgreSQL compatibility, strong consistency, and the flexibility of SQL for reporting and evolving queries. The most common Aurora complaint is that Serverless v2 retains a minimum idle cost and that I/O charges can surprise teams until they evaluate the I/O-Optimized tier. Sentiment across both is strongly workload-dependent: relational and analytical teams favor Aurora, while high-throughput key-value teams favor DynamoDB.

When to choose Amazon Aurora

Choose Amazon Aurora when your application is relational: normalized schemas, multi-table transactions, joins, and ad-hoc or reporting queries where access patterns evolve. It is also the natural target for migrating existing MySQL or PostgreSQL databases to a managed AWS service with minimal code change. Favor Aurora when SQL flexibility and strong relational consistency matter more than eliminating every minute of idle compute cost, and evaluate the I/O-Optimized tier for I/O-heavy workloads.

When to choose Amazon DynamoDB

Choose Amazon DynamoDB when you have well-defined key-value or document access patterns and need predictable single-digit-millisecond latency at large or unpredictable scale with minimal operations. It fits session stores, shopping carts, event ingestion, IoT telemetry, and serverless backends especially well, and on-demand mode keeps idle cost at zero. Confirm your queries fit partition-key design before committing, since ad-hoc joins and frequent access-pattern changes are where DynamoDB becomes harder to operate.

Alternatives to both