DBMS > Cubrid vs. Graph Engine

System Properties Comparison Cubrid vs. Graph Engine

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Our visitors often compare Cubrid and Graph Engine with Microsoft Azure Synapse Analytics, Adabas and PostgreSQL.

Editorial information provided by DB-Engines

Name

Description

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Primary database model

Relational DBMS

Graph DBMS
Key-value store

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Trend Chart

Score	1.00
Rank	#184	Overall
	#83	Relational DBMS

Score	0.58
Rank	#239	Overall
	#21	Graph DBMS
	#34	Key-value stores

Website

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

www.graphengine.io

Technical documentation

cubrid.org/manuals

www.graphengine.io/docs/manual

Developer

CUBRID Corporation, CUBRID Foundation

Microsoft

Initial release

2008

2010

Current release

11.0, January 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

MIT License

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

C, C++, Java

.NET and C

Server operating systems

Linux
Windows

.NET

Data scheme

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

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

RESTful HTTP API

Supported programming languages

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

C#
C++
F#
Visual Basic

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

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