DBMS > AnzoGraph DB vs. Microsoft Azure Data Explorer vs. MySQL vs. Stardog vs. Virtuoso

System Properties Comparison AnzoGraph DB vs. Microsoft Azure Data Explorer vs. MySQL vs. Stardog vs. Virtuoso

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

Fully managed big data interactive analytics platform

Widely used open source RDBMS

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Virtuoso is a multi-model hybrid-RDBMS that supports management of data represented as relational tables and/or property graphs

Primary database model

Graph DBMS
RDF store

Relational DBMS

column oriented

Relational DBMS

Key/Value like access via memcached API

Graph DBMS
RDF store

Document store
Graph DBMS
Native XML DBMS
Relational DBMS
RDF store
Search engine

Secondary database models

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine

support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

Document store
Spatial DBMS

Spatial 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	3.80
Rank	#81	Overall
	#43	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	4.27
Rank	#73	Overall
	#13	Document stores
	#4	Graph DBMS
	#2	Native XML DBMS
	#39	Relational DBMS
	#2	RDF stores
	#9	Search engines

Website

cambridgesemantics.com/anzograph

azure.microsoft.com/services/data-explorer

www.mysql.com

www.stardog.com

virtuoso.openlinksw.com

Technical documentation

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

docs.microsoft.com/en-us/azure/data-explorer

dev.mysql.com/doc

docs.stardog.com

docs.openlinksw.com/virtuoso

Developer

Cambridge Semantics

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Stardog-Union

OpenLink Software

Initial release

2018

2019

1995

2010

1998

Current release

2.3, January 2021

cloud service with continuous releases

8.4.0, April 2024

7.3.0, May 2020

7.2.11, September 2023

License

Commercial or Open Source

commercial

free trial version available

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Open Source

GPLv2, extended commercial license 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.

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

C and C++

Java

Server operating systems

Linux

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS
Windows

AIX
FreeBSD
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

Fixed schema with schema-less datatypes (dynamic)

yes

schema-free and OWL/RDFS-schema support

yes

SQL - Standard relational schema
RDF - Quad (S, P, O, G) or Triple (S, P, O)
XML - DTD, XML Schema
DAV - freeform filesystem objects, plus User Defined Types a/k/a Dynamic Extension Type

Typing

predefined data types such as float or date

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-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.

yes

Import/export of XML data possible

yes

Secondary indexes

all fields are automatically indexed

yes

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

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

Kusto Query Language (KQL), SQL subset

yes

with proprietary extensions

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

yes

SQL-92, SQL-200x, SQL-3, SQLX

APIs and other access methods

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

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

ADO.NET
GeoSPARQL
HTTP API
JDBC
Jena RDF API
ODBC
OLE DB
RDF4J API
RESTful HTTP API
Sesame REST HTTP Protocol
SOAP webservices
SPARQL 1.1
WebDAV
XPath
XQuery
XSLT

Supported programming languages

C++
Java
Python

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

.Net
C
C#
C++
Java
JavaScript
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

user defined functions and aggregates

Yes, possible languages: KQL, Python, R

yes

proprietary syntax

user defined functions and aggregates, HTTP Server extensions in Java

yes

Virtuoso PL

Triggers

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

yes

via event handlers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

Implicit feature of the cloud service

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

yes

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

Multi-source replication
Source-replica replication

Multi-source replication in HA-Cluster

Chain, star, and bi-directional replication
Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Spark connector (open source): github.com/Azure/azure-kusto-spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Eventual Consistency
Immediate Consistency

Immediate Consistency

Immediate Consistency in HA-Cluster

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

not for MyISAM storage engine

yes

relationships in graphs

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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.

yes

User concepts

Access control

Access rights for users and roles

Azure Active Directory Authentication

Users with fine-grained authorization concept

no user groups or roles

Access rights for users and roles

Fine-grained Attribute-Based Access Control (ABAC) in addition to typical coarse-grained Role-Based Access Control (RBAC) according to SQL-standard. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)

More information provided by the system vendor

Specific characteristics

Virtuoso is a modern multi-model RDBMS for managing data represented as tabular relations...
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Competitive advantages

Performance & Scale — as exemplified by DBpedia and the LOD Cloud it spawned, i.e.,...
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Typical application scenarios

Used for — Analytics/BI Conceptual Data Virtualization Enterprise Knowledge Graphs...
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Key customers

Broad use across enterprises and governments including — European Union (EU) US Government...
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Market metrics

Largest installed-base of Multi-Model RDBMS for AI-friendly Knowledge Graphs Platform...
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Licensing and pricing models

Available in both Commercial Enterprise and Open Source (GPL v2) Editions Feature...
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