DynamoDB vs Cosmos DB: what is the difference?

What each one is

DynamoDB is Amazon’s managed NoSQL database, built around a key-value and document model with single-digit-millisecond access patterns at scale — it is the database AWS itself uses for many of its own high-traffic services. Our what is Amazon DynamoDB explainer covers it in full. Cosmos DB is Microsoft’s managed NoSQL database, distinguished by supporting multiple data models — document, key-value, graph and column-family — through several APIs, and by offering global distribution and multi-region writes as a built-in, configurable feature rather than something bolted on afterwards.

Our relational vs NoSQL databases explainer covers what "NoSQL" means as a category and why both of these services trade some relational guarantees for horizontal scale and flexible schemas.

Key differences

The two diverge in a few concrete ways worth naming plainly:

• Data model — DynamoDB is key-value/document only; Cosmos DB is multi-model, exposing document, key-value, graph and column-family access through different APIs on the same underlying service.
• API surface — Cosmos DB deliberately offers multiple API options (including a document-style API and others aimed at easing migration from different database backgrounds); DynamoDB has one native API shaped around its own data model.
• Global distribution — Cosmos DB is built around turnkey multi-region replication with configurable consistency levels; DynamoDB offers global tables for multi-region replication too, but the multi-region story is more central to how Cosmos DB is marketed and configured from the outset.
• Ecosystem — DynamoDB is deeply wired into the rest of AWS (Lambda, IAM, API Gateway and so on); Cosmos DB is equally wired into Azure’s equivalent services. Neither runs natively outside its own cloud.

When to choose each

Choose DynamoDB when the workload already lives on AWS and needs a key-value or document store with predictable performance — serverless applications built on Lambda, session stores, and high-throughput application backends are common fits. Choose Cosmos DB when the workload is on Azure, or when the application genuinely needs more than one data model (for example, a graph alongside a document store) without standing up separate databases, or when multi-region, low-latency access from users spread across the globe is a first-class requirement from day one.

For most single-cloud teams, the honest answer is that the choice is already made by which cloud the rest of the application runs on — moving data across clouds just to use a "better" NoSQL database rarely pays for itself.

The honest framing: architecturally different, not a clear winner

Neither service is objectively "better" — they reflect different design philosophies. DynamoDB is narrower and deeply optimised for one data model within one cloud; Cosmos DB is broader, trading some of that focus for flexibility across data models and regions. Portability between the two is limited: application code written against DynamoDB’s API does not run against Cosmos DB’s APIs without rework, so this is not a decision to revisit lightly once an application is built around one of them.

Where this appears in cert study

DynamoDB is core material in the AWS Developer Associate and AWS Data Engineer Associate exams, covering data modelling, partition keys and capacity concepts. Cosmos DB appears in Azure’s data-focused exam paths and is touched on in the broader Azure Administrator Associate syllabus as one of Azure’s managed database options. Both exams expect you to recognise when a NoSQL database is the right fit compared with a relational one, more than to compare the two services against each other directly.