DBMS > Cubrid vs. HugeGraph vs. Newts

System Properties Comparison Cubrid vs. HugeGraph vs. Newts

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Name

Description

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

A fast-speed and highly-scalable Graph DBMS

Time Series DBMS based on Cassandra

Primary database model

Relational DBMS

Graph DBMS

Time Series DBMS

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

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

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

github.com/hugegraph
hugegraph.apache.org

opennms.github.io/newts

Technical documentation

cubrid.org/manuals

hugegraph.apache.org/docs

github.com/OpenNMS/newts/wiki

Developer

CUBRID Corporation, CUBRID Foundation

Baidu

OpenNMS Group

Initial release

2008

2018

2014

Current release

11.0, January 2021

0.9

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Open Source

Apache 2.0

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

Java

Server operating systems

Linux
Windows

Linux
macOS
Unix

Linux
OS X
Windows

Data scheme

yes

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

also supports composite index and range index

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

Java API
RESTful HTTP API
TinkerPop Gremlin

HTTP REST
Java API

Supported programming languages

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

Groovy
Java
Python

Java

Server-side scripts

Stored procedures

Java Stored Procedures

asynchronous Gremlin script jobs

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

depending on used storage backend, e.g. Cassandra and HBase

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

edges in graph

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

Users, roles and permissions

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More resources

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