DBMS > AnzoGraph DB vs. Cubrid vs. GigaSpaces vs. H2 vs. Microsoft SQL Server

System Properties Comparison AnzoGraph DB vs. Cubrid vs. GigaSpaces vs. H2 vs. Microsoft SQL Server

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

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Microsofts flagship relational DBMS

Primary database model

Graph DBMS
RDF store

Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Secondary database models

Graph DBMS
Search engine

Spatial DBMS

Document store
Graph DBMS
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	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

cambridgesemantics.com/anzograph

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

www.gigaspaces.com

www.h2database.com

www.microsoft.com/en-us/sql-server

Technical documentation

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

cubrid.org/manuals

docs.gigaspaces.com/latest/landing.html

www.h2database.com/html/main.html

learn.microsoft.com/en-US/sql/sql-server

Developer

Cambridge Semantics

CUBRID Corporation, CUBRID Foundation

Gigaspaces Technologies

Thomas Mueller

Microsoft

Initial release

2018

2008

2000

2005

1989

Current release

2.3, January 2021

11.0, January 2021

15.5, September 2020

2.2.220, July 2023

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache Version 2.0

Open Source

Apache Version 2; Commercial licenses available

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++, Java

Java, C++, .Net

Java

C++

Server operating systems

Linux

Linux
Windows

Linux
macOS
Solaris
Windows

All OS with a Java VM

Linux
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

yes

schema-free

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.

XML can be used for describing objects metadata

yes

Secondary indexes

yes

SQL

Support of SQL

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

yes

SQL-99 for query and DML statements

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

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

C++
Java
Python

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

.Net
C++
Java
Python
Scala

Java

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Server-side scripts

Stored procedures

user defined functions and aggregates

Java Stored Procedures

yes

Java Stored Procedures and User-Defined Functions

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

Sharding

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Source-replica replication

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

With clustering: 2 database servers on different computers operate on identical copies of a database

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Role-based access control

fine grained access rights according to SQL-standard

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