DBMS > AnzoGraph DB vs. H2 vs. Microsoft Azure SQL Database vs. Microsoft SQL Server vs. Valentina Server

System Properties Comparison AnzoGraph DB vs. H2 vs. Microsoft Azure SQL Database vs. Microsoft SQL Server vs. Valentina 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

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

Database as a Service offering with high compatibility to Microsoft SQL Server

Microsofts flagship relational DBMS

Object-relational database and reports server

Primary database model

Graph DBMS
RDF store

Relational DBMS

Secondary database models

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	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.17
Rank	#327	Overall
	#145	Relational DBMS

Website

cambridgesemantics.com/anzograph

www.h2database.com

azure.microsoft.com/en-us/products/azure-sql/database

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

www.valentina-db.net

Technical documentation

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

www.h2database.com/html/main.html

docs.microsoft.com/en-us/azure/azure-sql

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

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Cambridge Semantics

Thomas Mueller

Microsoft

Paradigma Software

Initial release

2018

2005

2010

1989

1999

Current release

2.3, January 2021

2.2.220, July 2023

V12

SQL Server 2022, November 2022

5.7.5

License

Commercial or Open Source

commercial

free trial version available

Open Source

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

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++

Server operating systems

Linux

All OS with a Java VM

hosted

Linux
Windows

Linux
OS X
Windows

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

APIs and other access methods

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

JDBC
ODBC

ADO.NET
JDBC
ODBC

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

ODBC

Supported programming languages

C++
Java
Python

Java

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

user defined functions and aggregates

Java Stored Procedures and User-Defined Functions

Transact SQL

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

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic 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

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

yes, with always 3 replicas available

yes, but depending on the SQL-Server Edition

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

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

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