DBMS > CouchDB vs. Dgraph vs. Microsoft Azure Cosmos DB vs. Microsoft Azure SQL Database vs. RDF4J

System Properties Comparison CouchDB vs. Dgraph vs. Microsoft Azure Cosmos DB vs. Microsoft Azure SQL Database vs. RDF4J

Editorial information provided by DB-Engines

Name

Description

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

Distributed and scalable native Graph DBMS

Globally distributed, horizontally scalable, multi-model database service

Database as a Service offering with high compatibility to Microsoft SQL Server

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

Primary database model

Document store

Graph DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

RDF store

Secondary database models

Spatial DBMS

using the Geocouch extension

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

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

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

couchdb.apache.org

dgraph.io

azure.microsoft.com/services/cosmos-db

azure.microsoft.com/en-us/products/azure-sql/database

rdf4j.org

Technical documentation

docs.couchdb.org/en/stable

dgraph.io/docs

learn.microsoft.com/azure/cosmos-db

docs.microsoft.com/en-us/azure/azure-sql

rdf4j.org/documentation

Developer

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Dgraph Labs, Inc.

Microsoft

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

Initial release

2005

2016

2014

2010

2004

Current release

3.3.3, December 2023

V12

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache 2.0

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

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++

Java

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

hosted

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

RDF Schemas

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.

yes

Secondary indexes

yes

via views

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

RESTful HTTP/JSON API

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

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

ADO.NET
JDBC
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

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

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

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

Java
PHP
Python

Server-side scripts

Stored procedures

View functions in JavaScript

JavaScript

Transact SQL

yes

Triggers

yes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

yes

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Synchronous replication via Raft

yes

Implicit feature of the cloud service

yes, with always 3 replicas available

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a single document possible

ACID

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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 for users can be defined per database

Planned for future releases

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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