DBMS > Microsoft Azure Cosmos DB vs. MonetDB vs. OrientDB vs. TerminusDB

System Properties Comparison Microsoft Azure Cosmos DB vs. MonetDB vs. OrientDB vs. TerminusDB

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Editorial information provided by DB-Engines

Name

Description

Globally distributed, horizontally scalable, multi-model database service

A relational database management system that stores data in columns

Multi-model DBMS (Document, Graph, Key/Value)

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Document store
Graph DBMS
Key-value store

Graph DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

Document store
RDF store

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

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

azure.microsoft.com/services/cosmos-db

www.monetdb.org

orientdb.org

terminusdb.com

Technical documentation

learn.microsoft.com/azure/cosmos-db

www.monetdb.org/Documentation

www.orientdb.com/docs/last/index.html

terminusdb.github.io/terminusdb/#

Developer

Microsoft

MonetDB BV

OrientDB LTD; CallidusCloud; SAP

DataChemist Ltd.

Initial release

2014

2004

2010

2018

Current release

Dec2023 (11.49), December 2023

3.2.29, March 2024

11.0.0, January 2023

License

Commercial or Open Source

commercial

Open Source

Mozilla Public License 2.0

Open Source

Apache version 2

Open Source

GPL V3

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

Prolog, Rust

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

All OS with a Java JDK (>= JDK 6)

Linux

Data scheme

schema-free

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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

SQL-like query language

yes

SQL 2003 with some extensions

SQL-like query language, no joins

SQL-like query language (WOQL)

APIs and other access methods

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

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

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

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

JavaScript
Python

Server-side scripts

Stored procedures

JavaScript

yes, in SQL, C, R

Java, Javascript

yes

Triggers

JavaScript

yes

Hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding via remote tables

Sharding

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

Source-replica replication available in experimental status

Multi-source replication

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory journaling

User concepts

Access control

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

Access rights for users and roles; record level security configurable

Role-based access control

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