DBMS > Amazon DocumentDB vs. Amazon DynamoDB vs. Microsoft Azure Cosmos DB vs. NSDb vs. VoltDB

System Properties Comparison Amazon DocumentDB vs. Amazon DynamoDB vs. Microsoft Azure Cosmos DB vs. NSDb vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

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

Globally distributed, horizontally scalable, multi-model database service

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Document store

Document store
Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	1.91
Rank	#131	Overall
	#24	Document stores

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

aws.amazon.com/documentdb

aws.amazon.com/dynamodb

azure.microsoft.com/services/cosmos-db

nsdb.io

www.voltdb.com

Technical documentation

aws.amazon.com/documentdb/resources

docs.aws.amazon.com/dynamodb

learn.microsoft.com/azure/cosmos-db

nsdb.io/Architecture

docs.voltdb.com

Developer

Amazon

Microsoft

VoltDB Inc.

Initial release

2019

2012

2014

2017

2010

Current release

11.3, April 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

Apache Version 2.0

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java, Scala

Java, C++

Server operating systems

hosted

Linux
macOS

Linux
OS X

for development

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

yes: int, bigint, decimal, string

yes

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

All properties auto-indexed by default

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

only a subset of SQL 99

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

RESTful HTTP API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

gRPC
HTTP REST
WebSocket

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Java
Scala

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

JavaScript

Java

Triggers

yes

by integration with AWS Lambda

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be specified for read operations

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

FOREIGN KEY constraints are not supported

Transaction concepts

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

Atomic single-document operations

ACID

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Using Apache Lucene

yes

Snapshots and command logging

User concepts

Access control

Access rights for users and roles

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

Access rights can be defined down to the item level

Users and roles with access to stored procedures

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