DBMS > IBM Cloudant vs. Microsoft Azure Cosmos DB vs. RDF4J vs. RocksDB vs. Tkrzw

System Properties Comparison IBM Cloudant vs. Microsoft Azure Cosmos DB vs. RDF4J vs. RocksDB vs. Tkrzw

Editorial information provided by DB-Engines

Name

Description

Database as a Service offering based on Apache CouchDB

Globally distributed, horizontally scalable, multi-model database service

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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Document store

Document store
Graph DBMS
Key-value store
Wide column store

RDF store

Key-value store

Secondary database models

Spatial DBMS

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

Score	2.68
Rank	#106	Overall
	#20	Document stores

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

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

www.ibm.com/products/cloudant

azure.microsoft.com/services/cosmos-db

rdf4j.org

rocksdb.org

dbmx.net/tkrzw

Technical documentation

cloud.ibm.com/docs/Cloudant

learn.microsoft.com/azure/cosmos-db

rdf4j.org/documentation

github.com/facebook/rocksdb/wiki

Developer

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Microsoft

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

Facebook, Inc.

Mikio Hirabayashi

Initial release

2010

2014

2004

2013

2020

Current release

8.11.4, April 2024

0.9.3, August 2020

License

Commercial or Open Source

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

BSD

Open Source

Apache Version 2.0

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

Java

C++

Server operating systems

hosted

Linux
OS X
Unix
Windows

Linux

Linux
macOS

Data scheme

schema-free

yes

RDF Schemas

schema-free

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

APIs and other access methods

RESTful HTTP/JSON API

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

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

C++ API
Java API

Supported programming languages

C#
Java
JavaScript
Objective-C
PHP
Ruby

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

Java
PHP
Python

C
C++
Go
Java
Perl
Python
Ruby

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

JavaScript

yes

Triggers

yes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

Implicit feature of the cloud service

none

yes

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

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

atomic operations within a document possible

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Isolation support depends on the API used

yes

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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.

yes

using specific database classes

User concepts

Access control

Access rights for users can be defined per database

Access rights can be defined down to the item level

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