Mongodb atlas vs mongodb aws

The following tables provide a comparison of MongoDB Community Server and MongoDB Atlas Enterprise features.

    DocumentDB and MongoDBArchitectureCompatibilityPerformanceDeploymentDeveloperOperationsPricing

Amazon DocumentDB instance pricing is more expensive than MongoDB Atlas, the fully managed MongoDB service. AWS DocumentDB starts at $200 per month for a single instance, with no free tier. Pricing is per instance-hour consumed, from the time an instance is launched until it is stopped or deleted. Partial instance hours are billed in one-second increments, but there is a 10-minute minimum charge following a billable status change such as creating, modifying, or deleting an instance.

Compare this with MongoDB Atlas, which has a perpetual free tier and starts at $9/mo for shared clusters, and around $60/mo for dedicated clusters.

The pricing comparison below is based on a default 3-node DocumentDB and MongoDB Atlas cluster, with backup storage equal to cluster storage. MongoDB Atlas is 8% to 19% less expensive.

Atlas price [per mo.]DocumentDB price% difference
15.25 GB RAM / 80 GB storage $567.46 $614.63 8.31%
30.5 GB RAM / 160 GB storage $1,086.73 $1,229.26 13.12%
61 GB RAM / 320 GB storage $2,147.20 $2,458.52 14.5%
122 GB RAM / 750 GB storage $4,143.36 $4,928.04 18.94%
244 GB RAM / 1.5 TB storage $8,277.95 $9,856.08 19.06%
488 GB RAM / 3 TB Storage $16,544.97 $19,712.16 19.14%

*Pricing correct as of September 2020

Convenience of a Single AWS Bill

MongoDB Atlas is available via the AWS Marketplace, providing streamlined procurement along with all other AWS services. Buying Atlas through the Marketplace enables customers to benefit from:

  • Consolidated billing through their AWS account

  • Retirement of their Amazon Enterprise Discount Program commitment

  • Simplified procurement with just a few clicks

  • Integration with AWS Marketplace catalogs and reports

  • A designated advisor from the AWS Marketplace team

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.

DocumentDB claims to support the MongoDB 4.0 API, which implies that it is at parity with MongoDB v4.0, released back in June 2018. In actual fact, the DocumentDB 4.0 feature set more closely resembles MongoDB 3.0 and 3.2, released in 2015. In addition, compatibility testing reveals it fails over 64% 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 DocumentDBMongoDB Atlas
Fully compatible with MongoDB

No, incomplete
Imitation API fails 64% of correctness tests

Yes
Support for latest MongoDB version

No
Feature set resembles MongoDB 3.0/3.2, released in 2015.

Yes
MongoDB 6.0

Scale writes and partition data beyond a single node / Sharding support

Limited
No sharding, single primary for write operations. Largest instance supports 30,000 concurrent connections.

Yes
Largest Atlas instance supports 128,000 concurrent connections. Full sharding support.

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

High resilience, rapid failure recovery, fast failover, retryable writes, multi-region

No
~120 second failover, no retryable writes, no multi-region in a single cluster

Yes
Typical failover sub-5 seconds, retryable reads and writes, multi-region & multi-cloud clusters

Multi-statement distributed ACID transactions

Limited
Ambiguous commits, poor error handling, small data sizes. Transactions unavailable as sharding is unsupported

Yes
Integrated text search, geospatial processing, graph traversals

Limited
Data replicated to multiple prerequisite bolt-on AWS services for text search, and only basic geospatial operators, adding cost and complexity

Yes
All available from a single API and platform

Native support for time series data No Yes

Hedged Reads

Queries submitted to multiple replicas for consistent low latency

No Yes

Online Archive

Automatically tier data out from database to cloud object storage [Amazon S3]

No

Yes
Online Archive

Integrated querying of data in Amazon S3

No
Data must be replicated to multiple adjacent AWS services, driving up cost and complexity

Yes
Atlas Query Federation

On-demand Materialized Views No

Yes
$merge aggregation stage

Schema governance

No
Schema controls must be enforced in the app

Yes
JSON schema

Rich data types

Limited
DocumentDB supports storing decimal128 values, but none of the powerful aggregation features for working with them.

Yes
Reactive, event-driven data pipelines

Limited
Change streams run against primary only & incur additional cost.

Yes
MongoDB Change Streams & Atlas Triggers

Support for role-based access control and authentication restrictions

Limited
Coarse-grained roles only

Yes
Client-side field level encryption for fine-grained separation of duties in the cloud No Yes
Availability of advanced developer and analysis tools Limited

Yes
MongoDB Compass, Charts, SQL Connector, Tableau Connector, Spark Connector

Fine-grained monitoring telemetry & prescriptive performance recommendations

No

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