DBMS > Cubrid vs. Hive vs. HugeGraph

System Properties Comparison Cubrid vs. Hive vs. HugeGraph

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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

data warehouse software for querying and managing large distributed datasets, built on Hadoop

A fast-speed and highly-scalable Graph DBMS

Primary database model

Relational DBMS

Graph DBMS

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

Score	1.31
Rank	#169	Overall
	#78	Relational DBMS

Score	62.59
Rank	#18	Overall
	#12	Relational DBMS

Score	0.15
Rank	#339	Overall
	#33	Graph DBMS

Website

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

hive.apache.org

github.com/hugegraph
hugegraph.apache.org

Technical documentation

cubrid.org/manuals

cwiki.apache.org/confluence/display/Hive/Home

hugegraph.apache.org/docs

Developer

CUBRID Corporation, CUBRID Foundation

Apache Software Foundation

initially developed by Facebook

Baidu

Initial release

2008

2012

2018

Current release

11.0, January 2021

3.1.3, April 2022

0.9

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2

Open Source

Apache Version 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

All OS with a Java VM

Linux
macOS
Unix

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

also supports composite index and range index

SQL

Support of SQL

yes

SQL-like DML and DDL statements

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

JDBC
ODBC
Thrift

Java API
RESTful HTTP API
TinkerPop Gremlin

Supported programming languages

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

C++
Java
PHP
Python

Groovy
Java
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes

user defined functions and integration of map-reduce

asynchronous Gremlin script jobs

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

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

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

yes

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

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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

Access rights for users, groups and roles

Users, roles and permissions

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