DBMS > AnzoGraph DB vs. FatDB vs. Microsoft Azure Table Storage vs. OrigoDB vs. Yaacomo

System Properties Comparison AnzoGraph DB vs. FatDB vs. Microsoft Azure Table Storage vs. OrigoDB vs. Yaacomo

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Yaacomo seems to be discontinued and is 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

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

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

A fully ACID in-memory object graph database

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Graph DBMS
RDF store

Document store
Key-value store

Wide column store

Document store
Object oriented DBMS

Relational 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	4.04
Rank	#77	Overall
	#6	Wide column stores

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

Website

cambridgesemantics.com/anzograph

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

origodb.com

yaacomo.com

Technical documentation

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

origodb.com/docs

Developer

Cambridge Semantics

FatCloud

Microsoft

Robert Friberg et al

Q2WEB GmbH

Initial release

2018

2012

2009

under the name LiveDB

2009

Current release

2.3, January 2021

License

Commercial or Open Source

commercial

free trial version available

commercial

Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Server operating systems

Linux

Windows

hosted

Linux
Windows

Android
Linux
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

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

Via inetgration in SQL Server

yes

APIs and other access methods

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

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

RESTful HTTP API

.NET Client API
HTTP API
LINQ

JDBC
ODBC

Supported programming languages

C++
Java
Python

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

.Net

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

via applications

yes

Triggers

yes

via applications

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

Implicit feature of the cloud service

horizontal partitioning

client side managed; servers are not synchronized

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

selectable replication factor

yes

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

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

depending on model

yes

Transaction concepts

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

ACID

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

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

Can implement custom security layer via applications

Access rights based on private key authentication or shared access signatures

Role based authorization

fine grained access rights according to SQL-standard

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