Comparing Amazon DocumentDB and MongoDB

What is DocumentDB?

Amazon DocumentDB is a NoSQL JSON document database service with a limited degree of compatibility with MongoDB.

DocumentDB is not based on the MongoDB server. Rather it emulates the MongoDB API, and runs on top of Amazon’s Aurora backend platform. This creates significant architectural constraints, functionality limitations, and broken compatibility.

The DocumentDB feature set most closely resembles MongoDB 2.6, introduced in 2014, and compatibility testing reveals it fails 61% of the MongoDB API correctness tests. Applications written for MongoDB will need to be re-written to work with Amazon DocumentDB.

Interested in up-to-date results on DocumentDB's compatibility with the MongoDB API? Get the latest results at Is DocumentDB Really MongoDB?

The key differences between DocumentDB and MongoDB’s on-demand, elastic, and fully managed Atlas service are summarized below.

Amazon DocumentDB
Fully compatible with MongoDBNo, fails 61% of correctness tests

Imitation API. Does not run MongoDB under the hood.

Yes
Support for latest MongoDB versionNo

Feature set resembles MongoDB 2.6, released in 2014.

Yes

MongoDB 4.2

Scale writes and partition data beyond a single nodeNo

Single primary only. Largest instance supports 4,500 concurrent connections

Yes

Largest Atlas instance supports 128,000 concurrent connections

Replicate and scale beyond a single region

Comply with data locality regulations and survive regional outages

No

Single primary constrained to a single region, with up to 15 replicas

Yes

Global clusters, with up to 50 replicas per shard across multiple regions

Rapid failure recovery

Fast failover and retryable writes

No

Up to 120 second failover, no retryable writes, no tolerance of single region failure

Yes

Typical failover of 5 seconds, with any failed writes auto-retried, multi-region deployments

Multi-statement ACID transactionsNo

Single statement only

Yes
Native text search, geospatial processing, graph traversalsNo

Data must be replicated to multiple adjacent AWS services, driving up cost and complexity

Yes

All available from a single API and platform

Integrated querying of data in Amazon S3No

Data must be replicated to separate AWS services

Yes

Atlas Data Lake

On-demand Materialized ViewsNoYes

$merge aggregation stage

Schema governance No

Schema controls must be enforced in the app

Yes

JSON schema

Rich data typesLimited

With no decimal data type, DocumentDB lacks support for lossless processing of complex numeric data

Yes
Reactive, event-driven data pipelinesLimited

Limited change streams

Yes

MongoDB Change Streams & Atlas Triggers

Support for role-based access control and authentication restrictionsNo

Users can only be created with full access to all databases in the cluster

Yes
Availability of advanced developer and analysis toolsNoYes

MongoDB Compass, Charts, BI Connector, Spark Connector

Fine-grained monitoring telemetry & prescriptive performance recommendations No

Less than 30 metrics

Yes

More than 100 metrics
Performance Advisor for index recommendations

Freedom from vendor lock-in No

AWS only
Constrained to just 7 regions

Yes

AWS, Azure, and GCP
Fully-managed, on-demand service available on 60+ regions

Develop & run anywhere

On your mobile device, on your laptop, in your own data center, and in hybrid configurations

No

AWS only

Yes

MongoDB Realm
MongoDB Server

Access to MongoDB expertiseNoYes

Hundreds of engineers with multi-year MongoDB development, support, and consulting experience

What is MongoDB Atlas?

MongoDB offers the fully managed, on-demand and global MongoDB Atlas service, in the public cloud. Atlas enables customers to deploy, operate, and scale MongoDB databases on AWS, Azure, or GCP. MongoDB Atlas is available through a pay-as-you-go model and billed on an hourly basis. It’s easy to get started – use a simple GUI or programmatic API calls to select the public cloud provider, region, instance size, and features you need. MongoDB Atlas provides:

  • Automated database and infrastructure provisioning along with auto-scaling so teams can get the database resources they need, when they need them, and can elastically scale in response to application demands.

  • Security features to protect your data, with network isolation, fine-grained access control, auditing, and end-to-end encryption down to the level of individual fields. enabling you to comply with regulations such as ISO, HIPAA and GDPR. Built in replication both within and across regions for always-on availability.

  • Global Clusters for a fully managed, globally distributed database that provides low latency, responsive reads and writes to users anywhere, with strong data placement controls for regulatory compliance.

  • Combined transactional and analytical capabilities with Atlas Analytics Nodes to isolate analytics queries from operational workloads while providing real-time insight. Native MongoDB analytics tools, such as MongoDB Charts and MongoDB Connector for BI are configured to utilize Analytics Nodes by default.

  • Fully integrated native MongoDB data visualization tools – MongoDB Charts, which supports the full richness of the document model, including nested, hierarchical and geospatial data and provide embedding and sharing capabilities. Quickly build visualizations of your data without needing to deploy or manage any software or infrastructure.

  • Fully integrated MongoDB Atlas Data Lake which allows you to quickly and easily query data in any format on Amazon S3 using the MongoDB Query Language (MQL) and tools and get value from your data faster.

  • Fully managed backups with point in time recovery to protect against data corruption, and the ability to query backups in-place without full restores.

  • Fine-grained monitoring and customizable alerts for comprehensive performance visibility. Automated patching and single-click upgrades for new major versions of the database, enabling you to take advantage of the latest MongoDB features.

  • Access to the MongoDB Realm and Stitch application platform, with QueryAnywhere, Functions, and Atlas Triggers delivered in a completely serverless model.

  • The Full-Text Search service providing rich search capabilities against your fully managed databases with no additional infrastructure or systems to provision, manage, or scale.

  • Live migration to move your self-managed MongoDB clusters into the Atlas service or to move Atlas clusters between cloud providers.

  • Widespread coverage on the major cloud platforms with availability in 60+ cloud regions across Amazon Web Services, Microsoft Azure, and Google Cloud Platform. MongoDB Atlas delivers a consistent experience across each of the cloud platforms, ensuring developers can deploy wherever they need to, without compromising critical functionality or risking lock-in.

MongoDB Atlas is serving a vast range of workloads for startups, Fortune 500 companies, and government agencies, including mission-critical applications handling highly sensitive data in regulated industries. The developer experience across MongoDB Atlas and self-managed MongoDB is consistent, ensuring that you easily move from on-premises to the public cloud, and between providers as your needs evolve.

Beyond the database, the MongoDB Atlas Data Lake allows you to quickly and easily query data in any format on Amazon S3 using the MongoDB Query Language (MQL) and tools. You can spin up your data lake right alongside your Atlas OLTP clusters from a common UI. With Atlas Data Lake you can realize the value of your data lake faster: you don’t have to move data anywhere, you can work with complex data immediately in its native form, and with its fully-managed, serverless architecture, you control costs and remove the operational burden. DocumentDB offers no equivalent capability, and so users must spin up an entirely separate service with a different query language to access S3 data.

Built and run by the same team that develops the data platform, MongoDB Atlas is the best way to run MongoDB apps.

Fully managed MongoDB

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Included with your free cloud database:

  • 512 MB of Storage
  • Shared RAM
  • Highly available replica sets, end-to-end encryption, automated patches, REST API

Additionally, get access to the following when you launch a dedicated cluster:

  • 10 GB or more of storage
  • Dedicated RAM
  • Performance optimization tools
  • Backups & point-in-time recovery
  • Enterprise security features including encryption key management, LDAP integration, and granular database auditing
  • Global Clusters