DBMS > Microsoft Azure SQL Database vs. SiteWhere vs. Spark SQL vs. Stardog vs. VoltDB

System Properties Comparison Microsoft Azure SQL Database vs. SiteWhere vs. Spark SQL vs. Stardog vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

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

M2M integration platform for persisting/querying time series data

Spark SQL is a component on top of 'Spark Core' for structured data processing

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

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

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	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

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

github.com/sitewhere/sitewhere

spark.apache.org/sql

www.stardog.com

www.voltdb.com

Technical documentation

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

sitewhere1.sitewhere.io/index.html

spark.apache.org/docs/latest/sql-programming-guide.html

docs.stardog.com

docs.voltdb.com

Developer

Microsoft

SiteWhere

Apache Software Foundation

Stardog-Union

VoltDB Inc.

Initial release

2010

2014

2010

Current release

V12

3.5.0 ( 2.13), September 2023

7.3.0, May 2020

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

Common Public Attribution License Version 1.0

Open Source

Apache 2.0

commercial

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

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

Scala

Java

Java, C++

Server operating systems

hosted

Linux
OS X
Windows

Linux
macOS
Windows

Linux
OS X

for development

Data scheme

yes

predefined scheme

yes

schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

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

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

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

yes

only a subset of SQL 99

APIs and other access methods

ADO.NET
JDBC
ODBC

HTTP REST

JDBC
ODBC

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

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

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

Java
Python
R
Scala

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Transact SQL

user defined functions and aggregates, HTTP Server extensions in Java

Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on HBase

yes, utilizing Spark Core

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with always 3 replicas available

selectable replication factor

based on HBase

none

Multi-source replication in HA-Cluster

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

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

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

Access rights for users and roles

Users and roles with access to stored procedures

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