DynamoDB vs Azure Cosmos DB
DynamoDB and Azure Cosmos DB are the flagship managed NoSQL databases of AWS and Azure. Both are fully managed and can run serverless, partition data by key, and scale horizontally. The biggest practical differences are cloud alignment, Cosmos DB's multi-model APIs and five tunable consistency levels, and how each bills for throughput.
Should you use DynamoDB or Cosmos DB?
Choose DynamoDB if you are on AWS and want a serverless key-value and document store with pay-per-request billing and deep AWS integration. Choose Azure Cosmos DB if you are on Azure, want multi-model APIs (document, Cassandra, Gremlin graph, Table), five explicit consistency levels, or turnkey multi-region writes. Cloud alignment usually decides it before features do.
DynamoDB vs Cosmos DB at a glance
| Characteristic | DynamoDB | Azure Cosmos DB |
|---|---|---|
| Data model | NoSQL key-value and document; items up to 400 KB in tables | Multi-model; the native API for NoSQL stores JSON documents, plus wire-compatible APIs for MongoDB, Cassandra, Gremlin (graph) and Table |
| Query language / API | Native API (GetItem, Query, Scan) plus PartiQL, a SQL-compatible language | SQL-like query language over JSON in the NoSQL API, plus each compatibility API's own query language |
| Partitioning / keys | Partition key with an optional sort key for a composite primary key | Partition key per container; items grouped into logical partitions |
| Consistency | Eventually consistent by default; strongly consistent reads available per request | Five levels — strong, bounded staleness, session, consistent prefix, eventual — chosen at the account or request level |
| Multi-region writes | Global Tables provide multi-Region, active-active replication | Turnkey global distribution; can enable multi-region writes (which precludes the strong consistency level) |
| Scaling model | Automatic partitioning; serverless on-demand or provisioned capacity | Provisioned throughput (RU/s), autoscale, or serverless; capacity measured in Request Units |
| Transactions | ACID transactions across multiple items within a Region | ACID transactions within a logical partition (e.g. transactional batch / stored procedures) |
| Pricing model | Pay-per-request (on-demand) or provisioned RCU/WCU, plus storage; AWS-only | Request Units per second (provisioned, autoscale, or serverless) plus storage, billed across every enabled region |
| Best-fit workloads | AWS-based apps with predictable key access wanting zero-ops serverless NoSQL | Azure-based apps wanting multi-model APIs, explicit consistency tuning, or global multi-write distribution |
When DynamoDB is the better choice
- You are on AWS. DynamoDB integrates natively with IAM, Lambda, Streams, and the wider AWS ecosystem, removing glue code you would otherwise write.
- You want simple pay-per-request pricing. On-demand capacity bills per read and write with no throughput to provision and no idle cost.
- Your access patterns are known and key-based. DynamoDB's partition/sort-key model delivers consistent low latency when you design keys around your queries — see single-table design.
- You want active-active multi-Region replication on AWS. Global Tables provide it as configuration.
When Cosmos DB is the better choice
- You are on Azure. Cosmos DB integrates with Azure identity, Functions, and the surrounding platform the way DynamoDB does with AWS.
- You need multi-model APIs. One service exposes document, Cassandra, Gremlin graph, and Table APIs, which can ease migrations from those ecosystems.
- You want explicit, tunable consistency. Cosmos DB offers five named consistency levels between strong and eventual — including bounded staleness and session — chosen per account or request.
- You need multi-region writes out of the box. Cosmos DB can accept writes in multiple regions with turnkey global distribution (at the cost of the strongest consistency level).
Working with DynamoDB
If you land on DynamoDB, DynoTable is a native desktop client for it on macOS, Windows, and Linux. It reads your standard AWS credential chain, so your data stays in DynamoDB with nothing to migrate. Beyond browsing and inline-editing items, its SQL Workbench expresses relational-shaped queries — joins, GROUP BY, aggregates — within DynamoDB's access-pattern rules by compiling them to Query/Scan, and its AI assistant runs on your own AWS Bedrock credentials.
The free DynamoDB Expression Builder generates key-condition, filter, and update expressions with correct reserved-word and attribute-name handling in SDK, CLI, and PartiQL form. DynoTable is a closed-source commercial app; this page describes what it does, not how it is built.
FAQ
Is Cosmos DB the same as DynamoDB?
No. They are separate products from Microsoft and AWS. Both are managed, serverless-capable NoSQL databases that partition by key, but Cosmos DB is multi-model with several wire-compatible APIs and five consistency levels, while DynamoDB is a key-value and document store native to AWS with a two-level (eventual or strong) read model and PartiQL.
Does DynamoDB have consistency levels like Cosmos DB?
DynamoDB offers two read modes rather than five named levels: eventually consistent reads (the default) and strongly consistent reads chosen per request within a Region. Cosmos DB exposes a spectrum — strong, bounded staleness, session, consistent prefix, and eventual — configured at the account or request level.
Can I migrate from Cosmos DB to DynamoDB?
You can, but plan for remodelling rather than a lift-and-shift. Both are key-partitioned NoSQL, so the concepts transfer, but you re-map partition/sort keys and rewrite queries to DynamoDB's API or PartiQL, and any Cosmos DB Gremlin or Cassandra API usage needs a different data model on DynamoDB. Start from your access patterns — see how to model data in DynamoDB.
Related
- Learn about DynamoDB consistency and multi-Region Global Tables.
- Model access patterns with single-table design and how to model data in DynamoDB.
- Build expressions with the free DynamoDB Expression Builder.
- Download DynoTable to work with your DynamoDB tables.
Last verified 2026-07-12 against the official AWS DynamoDB Developer Guide and Microsoft Azure Cosmos DB documentation. Azure Cosmos DB is a trademark of Microsoft; referenced here for identification only.