DBMS > AnzoGraph DB vs. Cubrid vs. MySQL vs. SAP HANA vs. StarRocks

System Properties Comparison AnzoGraph DB vs. Cubrid vs. MySQL vs. SAP HANA vs. StarRocks

Editorial information provided by DB-Engines

Name

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

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

Widely used open source RDBMS

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

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

Primary database model

Graph DBMS
RDF store

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Document store
Spatial 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	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	1.04
Rank	#189	Overall
	#88	Relational DBMS

Website

cambridgesemantics.com/anzograph

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

www.mysql.com

www.sap.com/products/hana.html

www.starrocks.io

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

cubrid.org/manuals

dev.mysql.com/doc

help.sap.com/hana

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

Developer

Cambridge Semantics

CUBRID Corporation, CUBRID Foundation

Oracle

since 2010, originally MySQL AB, then Sun

SAP

The Linux Foundation

since Feb 2023

Initial release

2018

2008

1995

2010

2020

Current release

2.3, January 2021

11.0, January 2021

8.4.0, April 2024

2.0 SPS07 (April 4, 2023), April 2023

2.5.3, March 2023

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache Version 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

also available as a cloud based service

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Implementation language

C, C++, Java

C and C++

C++, Java

Server operating systems

Linux

Linux
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Appliance or cloud-service

Linux

Data scheme

Schema-free and OWL/RDFS-schema support

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

yes

with proprietary extensions

yes

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

ADO.NET
JDBC
ODBC
OLE DB

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
ODBC

JDBC
MySQL protocol

Supported programming languages

C++
Java
Python

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Java

Server-side scripts

Stored procedures

user defined functions and aggregates

Java Stored Procedures

yes

proprietary syntax

SQLScript, R

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

yes

horizontal partitioning (by range and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Source-replica replication

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Access rights for users and roles

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

yes

Role based access control and fine grained access rights

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