DBMS > Amazon DynamoDB vs. Fauna vs. MongoDB

System Properties Comparison Amazon DynamoDB vs. Fauna vs. MongoDB

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Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

Primary database model

Document store
Key-value store

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Document store

Secondary database models

Spatial DBMS
Search engine

integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS

Time Series Collections introduced in Release 5.0

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	77.45
Rank	#16	Overall
	#2	Document stores
	#2	Key-value stores

Score	1.74
Rank	#158	Overall
	#26	Document stores
	#12	Graph DBMS
	#76	Relational DBMS
	#13	Time Series DBMS

Score	441.90
Rank	#5	Overall
	#1	Document stores

Website

aws.amazon.com/dynamodb

fauna.com

www.mongodb.com

Technical documentation

docs.aws.amazon.com/dynamodb

docs.fauna.com

docs.mongodb.com/manual

Developer

Amazon

Fauna, Inc.

MongoDB, Inc

Initial release

2012

2014

2009

Current release

6.0.1, August 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

Cloud-based only

Only available as a cloud service

yes

MongoDB available as DBaaS (MongoDB Atlas)

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Implementation language

Scala

C++

Server operating systems

hosted

Linux
OS X
Solaris
Windows

Data scheme

schema-free

Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.

Typing

predefined data types such as float or date

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

Read-only SQL queries via the MongoDB Connector for BI

APIs and other access methods

RESTful HTTP API

proprietary protocol using JSON

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

Actionscript

unofficial driver
C
C#
C++
Clojure

unofficial driver
ColdFusion

unofficial driver
D

unofficial driver
Dart

unofficial driver
Delphi

unofficial driver
Erlang
Go
Groovy

unofficial driver
Haskell
Java
JavaScript
Lisp

unofficial driver
Lua

unofficial driver
MatLab

unofficial driver
Perl
PHP
PowerShell

unofficial driver
Prolog

unofficial driver
Python
R

unofficial driver
Ruby
Rust
Scala
Smalltalk

unofficial driver
Swift

Server-side scripts

Stored procedures

user defined functions

JavaScript

Triggers

yes

by integration with AWS Lambda

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

consistent hashing

Sharding

Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Foreign keys

Referential integrity

yes

typically not used, however similar functionality with DBRef possible

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

ACID across one or more tables within a single AWS account and region

ACID

Multi-document ACID Transactions with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional, enabled by default

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

In-memory storage engine introduced with MongoDB version 3.2

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Identity management, authentication, and access control

Access rights for users and roles

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