DBMS > Amazon DocumentDB vs. AnzoGraph DB vs. IBM Cloudant vs. Microsoft Azure Cosmos DB vs. NuoDB

System Properties Comparison Amazon DocumentDB vs. AnzoGraph DB vs. IBM Cloudant vs. Microsoft Azure Cosmos DB vs. NuoDB

Editorial information provided by DB-Engines

Name

Description

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

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

Database as a Service offering based on Apache CouchDB

Globally distributed, horizontally scalable, multi-model database service

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Primary database model

Document store

Graph DBMS
RDF store

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	1.89
Rank	#137	Overall
	#24	Document stores

Score	0.27
Rank	#302	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	2.73
Rank	#108	Overall
	#20	Document stores

Score	29.85
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.99
Rank	#195	Overall
	#92	Relational DBMS

Website

aws.amazon.com/documentdb

cambridgesemantics.com/anzograph

www.ibm.com/products/cloudant

azure.microsoft.com/services/cosmos-db

www.3ds.com/nuodb-distributed-sql-database

Technical documentation

aws.amazon.com/documentdb/resources

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

cloud.ibm.com/docs/Cloudant

learn.microsoft.com/azure/cosmos-db

doc.nuodb.com

Developer

Cambridge Semantics

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Microsoft

Dassault Systèmes

originally NuoDB, Inc.

Initial release

2019

2018

2010

2014

2013

Current release

2.3, January 2021

License

Commercial or Open Source

commercial

free trial version available

commercial

limited edition free

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

Erlang

C++

Server operating systems

hosted

Linux

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Data scheme

schema-free

Schema-free and OWL/RDFS-schema support

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

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

yes

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

SQL-like query language

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

RESTful HTTP/JSON API

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

ADO.NET
JDBC
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

C++
Java
Python

C#
Java
JavaScript
Objective-C
PHP
Ruby

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

.Net
C
C++
Go
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions and aggregates

View functions (Map-Reduce) in JavaScript

JavaScript

Java, SQL

Triggers

yes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

none

Automatic sharding

Sharding

Implicit feature of the cloud service

data is dynamically stored/cached on the nodes where it is read/written

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication in MPP-Cluster

Multi-source replication
Source-replica replication

yes

Implicit feature of the cloud service

yes

Managed transparently by NuoDB

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Kerberos/HDFS data loading

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in MPP-Cluster

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

not needed in graphs

yes

Transaction concepts

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

Atomic single-document operations

ACID

atomic operations within a document possible

Multi-item ACID transactions with snapshot isolation within a partition

ACID

tunable commit protocol

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

MVCC

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

Temporary table

User concepts

Access control

Access rights for users and roles

Access rights for users can be defined per database

Access rights can be defined down to the item level

Standard SQL roles/ privileges, Administrative Users

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