DBMS > Amazon Redshift vs. Microsoft Azure AI Search vs. Quasardb vs. Riak KV vs. SiteWhere

System Properties Comparison Amazon Redshift vs. Microsoft Azure AI Search vs. Quasardb vs. Riak KV vs. SiteWhere

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

Distributed, high-performance timeseries database

Distributed, fault tolerant key-value store

M2M integration platform for persisting/querying time series data

Primary database model

with links between data sets and object tags for the creation of secondary indexes

Time Series DBMS

Secondary database models

Vector DBMS

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

Score	19.03
Rank	#34	Overall
	#21	Relational DBMS

Score	5.71
Rank	#64	Overall
	#8	Search engines

Score	0.19
Rank	#327	Overall
	#30	Time Series DBMS

Score	4.44
Rank	#80	Overall
	#9	Key-value stores

Score	0.06
Rank	#367	Overall
	#36	Time Series DBMS

Website

aws.amazon.com/redshift

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

quasar.ai

github.com/sitewhere/sitewhere

Technical documentation

docs.aws.amazon.com/redshift

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

doc.quasar.ai/master

www.tiot.jp/riak-docs/riak/kv/latest

sitewhere1.sitewhere.io/index.html

Developer

Amazon (based on PostgreSQL)

Microsoft

quasardb

OpenSource, formerly Basho Technologies

SiteWhere

Initial release

2012

2015

2009

2010

Current release

3.14.1, January 2024

3.2.0, December 2022

License

Commercial or Open Source

commercial

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

Open Source

Apache version 2, commercial enterprise edition

Open Source

Common Public Attribution License Version 1.0

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++

Erlang

Java

Server operating systems

hosted

BSD
Linux
OS X
Windows

Linux
OS X

Linux
OS X
Windows

Data scheme

yes

schema-free

predefined scheme

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.

Secondary indexes

restricted

yes

with tags

restricted

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

HTTP API

HTTP API
Native Erlang Interface

HTTP REST

Supported programming languages

All languages supporting JDBC/ODBC

C#
Java
JavaScript
Python

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

user defined functions

in Python

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

consistent hashing

Sharding

no "single point of failure"

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Source-replica replication with selectable replication factor

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

links between data sets can be stored

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

User concepts

Access control

fine grained access rights according to SQL-standard

yes

using Azure authentication

Cryptographically strong user authentication and audit trail

yes, using Riak Security

Users with fine-grained authorization concept

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