DBMS > Amazon Redshift vs. EXASOL vs. Kinetica vs. Microsoft Azure AI Search

System Properties Comparison Amazon Redshift vs. EXASOL vs. Kinetica vs. Microsoft Azure AI Search

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Fully vectorized database across both GPUs and CPUs

Search-as-a-service for web and mobile app development

Primary database model

Relational DBMS

Search engine

Secondary database models

Spatial DBMS
Time Series DBMS

Vector DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	5.59
Rank	#63	Overall
	#7	Search engines

Website

aws.amazon.com/redshift

www.exasol.com

www.kinetica.com

azure.microsoft.com/en-us/services/search

Technical documentation

docs.aws.amazon.com/redshift

www.exasol.com/resources

docs.kinetica.com

learn.microsoft.com/en-us/azure/search

Developer

Amazon (based on PostgreSQL)

Exasol

Kinetica

Microsoft

Initial release

2012

2000

2012

2015

Current release

7.1, August 2021

License

Commercial or Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

Server operating systems

hosted

Linux

hosted

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

.Net
JDBC
ODBC
WebSocket

JDBC
ODBC
RESTful HTTP API

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

Java
Lua
Python
R

C++
Java
JavaScript (Node.js)
Python

C#
Java
JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

Triggers

yes

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

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

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

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

Access rights for users and roles on table level

yes

using Azure authentication

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