DBMS > AnzoGraph DB vs. Faircom DB vs. Microsoft Access vs. OrigoDB

System Properties Comparison AnzoGraph DB vs. Faircom DB vs. Microsoft Access vs. OrigoDB

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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

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

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 fully ACID in-memory object graph database

Primary database model

Graph DBMS
RDF store

Key-value store
Relational DBMS

Relational DBMS

Document store
Object oriented 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	0.29
Rank	#304	Overall
	#43	Key-value stores
	#136	Relational DBMS

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Website

cambridgesemantics.com/anzograph

www.faircom.com/products/faircom-db

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

origodb.com

Technical documentation

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

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

developer.microsoft.com/en-us/access

origodb.com/docs

Developer

Cambridge Semantics

FairCom Corporation

Microsoft

Robert Friberg et al

Initial release

2018

1979

1992

2009

under the name LiveDB

Current release

2.3, January 2021

V12, November 2020

1902 (16.0.11328.20222), March 2019

License

Commercial or Open Source

commercial

free trial version available

commercial

Restricted, free version available

commercial

Bundled with Microsoft Office

Open Source

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

ANSI C, C++

C++

Server operating systems

Linux

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

Windows

Not a real database server, but making use of DLLs

Linux
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

schema free, schema optional, schema required, partial schema,

yes

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

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

yes, ANSI SQL with proprietary extensions

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

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

ADO.NET
DAO
ODBC
OLE DB

.NET Client API
HTTP API
LINQ

Supported programming languages

C++
Java
Python

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

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

.Net

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

.Net, JavaScript, C/C++

yes

since Access 2010 using the ACE-engine

yes

Triggers

yes

since Access 2010 using the ACE-engine

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

none

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

none

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

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Foreign keys

Referential integrity

not needed in graphs

yes

depending on model

Transaction concepts

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

ACID

tunable from ACID to Eventually Consistent

ACID

but no files for transaction logging

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Yes, tunable from durable to delayed durability to in-memory

yes

but no files for transaction logging

yes

Write ahead log

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 with additional protections for files

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

Role based authorization

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More resources

DB-Engines blog posts

MS Access drops in DB-Engines Ranking
2 May 2013, Paul Andlinger

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3 December 2012, Matthias Gelbmann

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3 October 2012, Matthias Gelbmann, Paul Andlinger

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