DBMS > Galaxybase vs. IBM Cloudant vs. RDFox vs. Spark SQL

System Properties Comparison Galaxybase vs. IBM Cloudant vs. RDFox vs. Spark SQL

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Editorial information provided by DB-Engines

Name

Description

Scalable, ACID-compliant native distributed parallel graph platform

Database as a Service offering based on Apache CouchDB

High performance knowledge graph and semantic reasoning engine

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Secondary database models

Relational DBMS

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

Score	0.07
Rank	#377	Overall
	#40	Graph DBMS

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	0.29
Rank	#300	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Website

galaxybase.com

www.ibm.com/products/cloudant

www.oxfordsemantic.tech

spark.apache.org/sql

Technical documentation

cloud.ibm.com/docs/Cloudant

docs.oxfordsemantic.tech

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Oxford Semantic Technologies

Apache Software Foundation

Initial release

2017

2010

2017

2014

Current release

Nov 20, November 2021

6.0, Septermber 2022

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

Apache 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

C and Java

Erlang

C++

Scala

Server operating systems

Linux

hosted

Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

Strong typed schema

schema-free

yes

RDF schemas

yes

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

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

RESTful HTTP/JSON API

RESTful HTTP API
SPARQL 1.1

JDBC
ODBC

Supported programming languages

Go
Java
Python

C#
Java
JavaScript
Objective-C
PHP
Ruby

C
Java

Java
Python
R
Scala

Server-side scripts

Stored procedures

user defined procedures and functions

View functions (Map-Reduce) in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

replication via a shared file system

none

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

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

atomic operations within a document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

Role-based access control

Access rights for users can be defined per database

Roles, resources, and access types

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