DBMS > Blazegraph vs. Microsoft Azure Cosmos DB vs. mSQL vs. NuoDB

System Properties Comparison Blazegraph vs. Microsoft Azure Cosmos DB vs. mSQL vs. NuoDB

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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.

Description

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

Globally distributed, horizontally scalable, multi-model database service

mSQL (Mini SQL) is a simple and lightweight RDBMS

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Primary database model

Graph DBMS
RDF store

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.75
Rank	#219	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Website

blazegraph.com

azure.microsoft.com/services/cosmos-db

hughestech.com.au/products/msql

www.3ds.com/nuodb-distributed-sql-database

Technical documentation

wiki.blazegraph.com

learn.microsoft.com/azure/cosmos-db

doc.nuodb.com

Developer

Blazegraph

Microsoft

Hughes Technologies

Dassault Systèmes

originally NuoDB, Inc.

Initial release

2006

2014

1994

2013

Current release

2.1.5, March 2019

4.4, October 2021

License

Commercial or Open Source

Open Source

extended commercial license available

commercial

free licenses can be provided

commercial

limited edition free

Cloud-based only

Only available as a cloud service

yes

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Database as a Service

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Implementation language

Java

C++

Server operating systems

Linux
OS X
Windows

hosted

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

RDF literal types

yes

JSON types

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.

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SPARQL is used as query language

SQL-like query language

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

APIs and other access methods

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

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

JDBC
ODBC

ADO.NET
JDBC
ODBC

Supported programming languages

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

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

C
C++
Delphi
Java
Perl
PHP
Tcl

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

Server-side scripts

Stored procedures

yes

JavaScript

Java, SQL

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

data is dynamically stored/cached on the nodes where it is read/written

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

yes

Managed transparently by NuoDB

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in Graphs

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

ACID

tunable commit protocol

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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.

yes

Temporary table

User concepts

Access control

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

Access rights can be defined down to the item level

Standard SQL roles/ privileges, Administrative Users

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