DBMS > Cubrid vs. HugeGraph vs. Kinetica vs. SAP HANA

System Properties Comparison Cubrid vs. HugeGraph vs. Kinetica vs. SAP HANA

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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

A fast-speed and highly-scalable Graph DBMS

Fully vectorized database across both GPUs and CPUs

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Relational DBMS

Graph DBMS

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

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

github.com/hugegraph
hugegraph.apache.org

www.kinetica.com

www.sap.com/products/hana.html

Technical documentation

cubrid.org/manuals

hugegraph.apache.org/docs

docs.kinetica.com

help.sap.com/hana

Developer

CUBRID Corporation, CUBRID Foundation

Baidu

Kinetica

SAP

Initial release

2008

2018

2012

2010

Current release

11.0, January 2021

0.9

7.1, August 2021

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++, Java

Java

C, C++

Server operating systems

Linux
Windows

Linux
macOS
Unix

Linux

Appliance or cloud-service

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

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

Supported programming languages

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

Groovy
Java
Python

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Java Stored Procedures

asynchronous Gremlin script jobs

user defined functions

SQLScript, R

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

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

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

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

Source-replica replication

yes

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

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

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

GPU vRAM or System RAM

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Users, roles and permissions

Access rights for users and roles on table level

yes

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