DBMS > Blazegraph vs. FatDB vs. gStore vs. Microsoft Azure Cosmos DB

System Properties Comparison Blazegraph vs. FatDB vs. gStore vs. Microsoft Azure Cosmos DB

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Editorial information provided by DB-Engines

Name

Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.

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

Description

High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.

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

A native Graph DBMS to store and maintain very large RDF datasets.

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Graph DBMS
RDF store

Document store
Key-value store

Graph DBMS
RDF store

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Spatial DBMS

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

Score	0.81
Rank	#213	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	0.14
Rank	#342	Overall
	#34	Graph DBMS
	#16	RDF stores

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

blazegraph.com

en.gstore.cn

azure.microsoft.com/services/cosmos-db

Technical documentation

wiki.blazegraph.com

en.gstore.cn/#/enDocs

learn.microsoft.com/azure/cosmos-db

Developer

Blazegraph

FatCloud

Microsoft

Initial release

2006

2012

2016

2014

Current release

2.1.5, March 2019

1.2, November 2023

License

Commercial or Open Source

Open Source

extended commercial license available

commercial

Open Source

BSD

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

Java

C++

Server operating systems

Linux
OS X
Windows

Windows

Linux

hosted

Data scheme

schema-free

schema-free and OWL/RDFS-schema support

schema-free

Typing

predefined data types such as float or date

yes

RDF literal types

yes

JSON types

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.

Secondary indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

SPARQL is used as query language

Via inetgration in SQL Server

SQL-like query language

APIs and other access methods

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

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

HTTP API
SPARQL 1.1

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Supported programming languages

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

C++
Java
JavaScript (Node.js)
PHP
Python

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Server-side scripts

Stored procedures

yes

via applications

yes

JavaScript

Triggers

yes

via applications

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

Relationships in Graphs

Transaction concepts

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

ACID

yes

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

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.

User concepts

Access control

Security and Authentication via Web Application Container (Tomcat, Jetty)

Can implement custom security layer via applications

Users, roles and permissions, Role-Based Access Control (RBAC) supported

Access rights can be defined down to the item level

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