DBMS > Blazegraph vs. Microsoft Azure Cosmos DB vs. MonetDB vs. Quasardb vs. Sphinx

System Properties Comparison Blazegraph vs. Microsoft Azure Cosmos DB vs. MonetDB vs. Quasardb vs. Sphinx

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

A relational database management system that stores data in columns

Distributed, high-performance timeseries database

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Graph DBMS
RDF store

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Time Series DBMS

Search engine

Secondary database models

Spatial DBMS

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

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

blazegraph.com

azure.microsoft.com/services/cosmos-db

www.monetdb.org

quasar.ai

sphinxsearch.com

Technical documentation

wiki.blazegraph.com

learn.microsoft.com/azure/cosmos-db

www.monetdb.org/Documentation

doc.quasar.ai/master

sphinxsearch.com/docs

Developer

Blazegraph

Microsoft

MonetDB BV

quasardb

Sphinx Technologies Inc.

Initial release

2006

2014

2004

2009

2001

Current release

2.1.5, March 2019

Dec2023 (11.49), December 2023

3.14.1, January 2024

3.5.1, February 2023

License

Commercial or Open Source

Open Source

extended commercial license available

commercial

Open Source

Mozilla Public License 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

GPL version 2, commercial licence available

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
OS X
Windows

hosted

FreeBSD
Linux
OS X
Solaris
Windows

BSD
Linux
OS X
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

RDF literal types

yes

JSON types

yes

integer and binary

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

with tags

yes

full-text index on all search fields

SQL

Support of SQL

SPARQL is used as query language

SQL-like query language

yes

SQL 2003 with some extensions

SQL-like query language

SQL-like query language (SphinxQL)

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
native C library

MAPI library (MonetDB application programming interface)
ODBC

HTTP API

Proprietary protocol

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++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

JavaScript

yes, in SQL, C, R

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding via remote tables

Sharding

consistent hashing

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

Source-replica replication available in experimental status

Source-replica replication with selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

with Hadoop integration

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

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

The original contents of fields are not stored in the Sphinx index.

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Transient mode

User concepts

Access control

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

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

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