DBMS > Amazon Redshift vs. Kinetica vs. Microsoft Azure SQL Database vs. Realm

System Properties Comparison Amazon Redshift vs. Kinetica vs. Microsoft Azure SQL Database vs. Realm

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Fully vectorized database across both GPUs and CPUs

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

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Primary database model

Relational DBMS

Document store

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Website

aws.amazon.com/redshift

www.kinetica.com

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

realm.io

Technical documentation

docs.aws.amazon.com/redshift

docs.kinetica.com

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

realm.io/docs

Developer

Amazon (based on PostgreSQL)

Kinetica

Microsoft

Realm, acquired by MongoDB in May 2019

Initial release

2012

2010

2014

Current release

7.1, August 2021

V12

License

Commercial or Open Source

commercial

Open Source

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, C++

C++

Server operating systems

hosted

Linux

hosted

Android
Backend: server-less
iOS
Windows

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

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

C++
Java
JavaScript (Node.js)
Python

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

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

Transact SQL

runs within the applications so server-side scripts are unnecessary

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes, with always 3 replicas available

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

GPU vRAM or System RAM

yes

In-Memory realm

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

yes

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