DBMS > AnzoGraph DB vs. Atos Standard Common Repository vs. dBASE vs. Google BigQuery vs. Microsoft Access

System Properties Comparison AnzoGraph DB vs. Atos Standard Common Repository vs. dBASE vs. Google BigQuery vs. Microsoft Access

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

dBase was one of the first databases with a development environment on PC's. Its latest version dBase V is still sold as dBase classic, which needs a DOS Emulation. The up-to-date product is dBase plus.

Large scale data warehouse service with append-only tables

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.)

Primary database model

Graph DBMS
RDF store

Document store
Key-value store

Relational 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	10.34
Rank	#44	Overall
	#28	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Website

cambridgesemantics.com/anzograph

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

www.dbase.com

cloud.google.com/bigquery

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

Technical documentation

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

www.dbase.com/support/knowledgebase

cloud.google.com/bigquery/docs

developer.microsoft.com/en-us/access

Developer

Cambridge Semantics

Atos Convergence Creators

Asthon Tate

Google

Microsoft

Initial release

2018

2016

1979

2010

1992

Current release

2.3, January 2021

1703

dBASE 2019, 2019

1902 (16.0.11328.20222), March 2019

License

Commercial or Open Source

commercial

free trial version available

commercial

Bundled with Microsoft Office

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

DOS

dBase Classic
Windows

dBase Pro

hosted

Windows

Not a real database server, but making use of DLLs

Data scheme

Schema-free and OWL/RDFS-schema support

Schema and schema-less with LDAP views

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

APIs and other access methods

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

LDAP

none

The IDE can access other DBMS or ODBC-sources.

RESTful HTTP/JSON API

ADO.NET
DAO
ODBC
OLE DB

Supported programming languages

C++
Java
Python

All languages with LDAP bindings

dBase proprietary IDE

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

user defined functions and aggregates

The IDE can access stored procedures in other database systems.

user defined functions

in JavaScript

yes

since Access 2010 using the ACE-engine

Triggers

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

cell division

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

yes

none

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

Transaction concepts

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

ACID

Atomic execution of specific operations

not for dBase internal data, but IDE does support transactions when accessing external DBMS

Since BigQuery is designed for querying data

ACID

but no files for transaction logging

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

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

Access rights for users and roles

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

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

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