DBMS > Microsoft Azure SQL Database vs. Microsoft SQL Server vs. Quasardb vs. Stardog vs. TempoIQ

System Properties Comparison Microsoft Azure SQL Database vs. Microsoft SQL Server vs. Quasardb vs. Stardog vs. TempoIQ

Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

Database as a Service offering with high compatibility to Microsoft SQL Server

Microsofts flagship relational DBMS

Distributed, high-performance timeseries database

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

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	78.40
Rank	#15	Overall
	#10	Relational DBMS

Score	829.80
Rank	#3	Overall
	#3	Relational DBMS

Score	0.19
Rank	#327	Overall
	#30	Time Series DBMS

Score	2.05
Rank	#129	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

azure.microsoft.com/en-us/products/azure-sql/database

www.microsoft.com/en-us/sql-server

quasar.ai

www.stardog.com

tempoiq.com (offline)

Technical documentation

docs.microsoft.com/en-us/azure/azure-sql

learn.microsoft.com/en-US/sql/sql-server

doc.quasar.ai/master

docs.stardog.com

Developer

Microsoft

quasardb

Stardog-Union

TempoIQ

Initial release

2010

1989

2009

2010

2012

Current release

V12

SQL Server 2022, November 2022

3.14.1, January 2024

7.3.0, May 2020

License

Commercial or Open Source

commercial

restricted free version is available

commercial

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

commercial

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

commercial

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

C++

Java

Server operating systems

hosted

Linux
Windows

BSD
Linux
OS X
Windows

Linux
macOS
Windows

Data scheme

yes

schema-free

schema-free and OWL/RDFS-schema support

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

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

Secondary indexes

yes

with tags

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

SQL-like query language

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

APIs and other access methods

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

HTTP API

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

HTTP API

Supported programming languages

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

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

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

Transact SQL

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with always 3 replicas available

yes, but depending on the SQL-Server Edition

Source-replica replication with selectable replication factor

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

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

yes

Transient mode

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

Access rights for users and roles

simple authentication-based access control

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