DBMS > Amazon Redshift vs. Microsoft SQL Server vs. SpaceTime

System Properties Comparison Amazon Redshift vs. Microsoft SQL Server vs. SpaceTime

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Microsofts flagship relational DBMS

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Primary database model

Relational DBMS

Spatial DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

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Trend Chart

Score	15.10
Rank	#38	Overall
	#23	Relational DBMS

Score	802.09
Rank	#3	Overall
	#3	Relational DBMS

Score	0.00
Rank	#388	Overall
	#7	Spatial DBMS

Website

aws.amazon.com/redshift

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

www.mireo.com/spacetime

Technical documentation

docs.aws.amazon.com/redshift

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

Developer

Amazon (based on PostgreSQL)

Microsoft

Mireo

Initial release

2012

1989

2020

Current release

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

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Implementation language

C++

Server operating systems

hosted

Linux
Windows

Linux

Data scheme

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

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

A subset of ANSI SQL is implemented

APIs and other access methods

JDBC
ODBC

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

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

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

C#
C++
Python

Server-side scripts

Stored procedures

user defined functions

in Python

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Fixed-grid hypercubes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, but depending on the SQL-Server Edition

Real-time block device replication (DRBD)

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

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

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

yes

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