DBMS > Cubrid vs. EXASOL vs. HEAVY.AI vs. RDFox

System Properties Comparison Cubrid vs. EXASOL vs. HEAVY.AI vs. RDFox

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Editorial information provided by DB-Engines

Name

Description

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

High performance knowledge graph and semantic reasoning engine

Primary database model

Relational DBMS

Graph DBMS
RDF store

Secondary database models

Spatial DBMS

Relational DBMS

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

Score	1.31
Rank	#169	Overall
	#78	Relational DBMS

Score	2.25
Rank	#120	Overall
	#57	Relational DBMS

Score	2.10
Rank	#126	Overall
	#61	Relational DBMS

Score	0.24
Rank	#309	Overall
	#25	Graph DBMS
	#14	RDF stores

Website

cubrid.com (korean)
cubrid.org (english)

www.exasol.com

github.com/heavyai/heavydb
www.heavy.ai

www.oxfordsemantic.tech

Technical documentation

cubrid.org/manuals

www.exasol.com/resources

docs.heavy.ai

docs.oxfordsemantic.tech

Developer

CUBRID Corporation, CUBRID Foundation

Exasol

HEAVY.AI, Inc.

Oxford Semantic Technologies

Initial release

2008

2000

2016

2017

Current release

11.0, January 2021

5.10, January 2022

6.0, Septermber 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2; enterprise edition available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++, Java

C++ and CUDA

C++

Server operating systems

Linux
Windows

Linux

Linux
macOS
Windows

Data scheme

yes

RDF schemas

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

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

.Net
JDBC
ODBC
WebSocket

JDBC
ODBC
Thrift
Vega

RESTful HTTP API
SPARQL 1.1

Supported programming languages

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

Java
Lua
Python
R

All languages supporting JDBC/ODBC/Thrift
Python

C
Java

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

replication via a shared file system

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

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

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

Roles, resources, and access types

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