DBMS > DataFS vs. IBM Cloudant vs. JaguarDB vs. RDF4J vs. Riak TS

System Properties Comparison DataFS vs. IBM Cloudant vs. JaguarDB vs. RDF4J vs. Riak TS

Editorial information provided by DB-Engines

Name

Description

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

Database as a Service offering based on Apache CouchDB

Performant, highly scalable DBMS for AI and IoT applications

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

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Object oriented DBMS

Document store

Key-value store
Vector DBMS

RDF store

Time Series DBMS

Secondary database models

Graph DBMS

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

Score	0.09
Rank	#360	Overall
	#18	Object oriented DBMS

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#15	Vector DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Website

newdatabase.com

www.ibm.com/products/cloudant

www.jaguardb.com

rdf4j.org

Technical documentation

dev.mobiland.com/Overview.xsp

cloud.ibm.com/docs/Cloudant

www.jaguardb.com/support.html

rdf4j.org/documentation

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Mobiland AG

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

DataJaguar, Inc.

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

Open Source, formerly Basho Technologies

Initial release

2018

2010

2015

2004

2015

Current release

1.1.263, October 2022

3.3 July 2023

3.0.0, September 2022

License

Commercial or Open Source

commercial

Open Source

GPL V3.0

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

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++

the server part. Clients available in other languages

Java

Erlang

Server operating systems

Windows

hosted

Linux

Linux
OS X
Unix
Windows

Linux
OS X

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

schema-free

yes

RDF Schemas

schema-free

Typing

predefined data types such as float or date

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

restricted

SQL

Support of SQL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes, limited

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

RESTful HTTP/JSON API

JDBC
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

HTTP API
Native Erlang Interface

Supported programming languages

.Net
C
C#
C++
VB.Net

C#
Java
JavaScript
Objective-C
PHP
Ruby

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

Java
PHP
Python

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

yes

Erlang

Triggers

no, except callback-events from server when changes happened

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

none

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

Transaction concepts

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

ACID

atomic operations within a document possible

ACID

Isolation support depends on the API used

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.

User concepts

Access control

Windows-Profile

Access rights for users can be defined per database

rights management via user accounts

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