DBMS > Microsoft Azure Cosmos DB vs. MonetDB vs. RDF4J vs. TigerGraph

System Properties Comparison Microsoft Azure Cosmos DB vs. MonetDB vs. RDF4J vs. TigerGraph

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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

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

RDF store

Graph DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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

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

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

azure.microsoft.com/services/cosmos-db

www.monetdb.org

rdf4j.org

www.tigergraph.com

Technical documentation

learn.microsoft.com/azure/cosmos-db

www.monetdb.org/Documentation

rdf4j.org/documentation

docs.tigergraph.com

Developer

Microsoft

MonetDB BV

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2014

2004

2017

Current release

Dec2023 (11.49), December 2023

License

Commercial or Open Source

commercial

Open Source

Mozilla Public License 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Unix
Windows

Linux

Data scheme

schema-free

yes

RDF Schemas

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 (GSQL)

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

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

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

Java
PHP
Python

C++
Java

Server-side scripts

Stored procedures

JavaScript

yes, in SQL, C, R

yes

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding via remote tables

none

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

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

Relationships in graphs

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

In-memory capabilities

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

User concepts

Access control

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

Role-based access control

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