DBMS > IBM Cloudant vs. RDF4J vs. SQream DB

System Properties Comparison IBM Cloudant vs. RDF4J vs. SQream DB

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Editorial information provided by DB-Engines

Name

Description

Database as a Service offering based on Apache CouchDB

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

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Document store

RDF store

Relational DBMS

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

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.70
Rank	#227	Overall
	#104	Relational DBMS

Website

www.ibm.com/products/cloudant

rdf4j.org

sqream.com

Technical documentation

cloud.ibm.com/docs/Cloudant

rdf4j.org/documentation

docs.sqream.com

Developer

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

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

SQream Technologies

Initial release

2010

2004

2017

Current release

2022.1.6, December 2022

License

Commercial or Open Source

commercial

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

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Erlang

Java

C++, CUDA, Haskell, Java, Scala

Server operating systems

hosted

Linux
OS X
Unix
Windows

Linux

Data scheme

schema-free

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP/JSON API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

.Net
JDBC
ODBC

Supported programming languages

C#
Java
JavaScript
Objective-C
PHP
Ruby

Java
PHP
Python

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

yes

user defined functions in Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual 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

ACID

Isolation support depends on the API used

ACID

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

Access rights for users can be defined per database

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More resources

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