DBMS > AnzoGraph DB vs. Atos Standard Common Repository vs. Microsoft Access vs. Microsoft Azure Table Storage vs. MySQL

System Properties Comparison AnzoGraph DB vs. Atos Standard Common Repository vs. Microsoft Access vs. Microsoft Azure Table Storage vs. MySQL

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

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

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

A Wide Column Store for rapid development using massive semi-structured datasets

Widely used open source RDBMS

Primary database model

Graph DBMS
RDF store

Document store
Key-value store

Relational DBMS

Wide column store

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store
Spatial DBMS

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

Score	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Website

cambridgesemantics.com/anzograph

atos.net/en/convergence-creators/portfolio/standard-common-repository

www.microsoft.com/en-us/microsoft-365/access

azure.microsoft.com/en-us/services/storage/tables

www.mysql.com

Technical documentation

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

developer.microsoft.com/en-us/access

dev.mysql.com/doc

Developer

Cambridge Semantics

Atos Convergence Creators

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2018

2016

1992

2012

1995

Current release

2.3, January 2021

1703

1902 (16.0.11328.20222), March 2019

8.4.0, April 2024

License

Commercial or Open Source

commercial

free trial version available

commercial

Bundled with Microsoft Office

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C++

C and C++

Server operating systems

Linux

Windows

Not a real database server, but making use of DLLs

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

Schema and schema-less with LDAP views

yes

schema-free

yes

Typing

predefined data types such as float or date

optional

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

but not compliant to any SQL standard

yes

with proprietary extensions

APIs and other access methods

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

LDAP

ADO.NET
DAO
ODBC
OLE DB

RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C++
Java
Python

All languages with LDAP bindings

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

.Net
C#
C++
Java
JavaScript (Node.js)
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

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

since Access 2010 using the ACE-engine

yes

proprietary syntax

Triggers

yes

since Access 2010 using the ACE-engine

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

cell division

none

Sharding

Implicit feature of the cloud service

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

yes

none

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Multi-source replication
Source-replica replication

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 or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

but no files for transaction logging

optimistic locking

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

but no files for transaction logging

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

LDAP bind authentication

a simple user-level security was built in till version Access 2003

Access rights based on private key authentication or shared access signatures

Users with fine-grained authorization concept

no user groups or roles

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