DBMS > Kinetica vs. Microsoft Azure AI Search vs. OpenSearch vs. Quasardb vs. SiteWhere

System Properties Comparison Kinetica vs. Microsoft Azure AI Search vs. OpenSearch vs. Quasardb vs. SiteWhere

Editorial information provided by DB-Engines

Name

Description

Fully vectorized database across both GPUs and CPUs

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

A distributed, RESTful search and analytics engine forked from Elasticsearch and based on Apache Lucene

Distributed, high-performance timeseries database

M2M integration platform for persisting/querying time series data

Primary database model

Relational DBMS

Search engine

Time Series DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

Vector DBMS

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

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	16.03
Rank	#37	Overall
	#4	Search engines

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Website

www.kinetica.com

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

github.com/opensearch-project
opensearch.org

quasar.ai

github.com/sitewhere/sitewhere

Technical documentation

docs.kinetica.com

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

opensearch.org/docs/latest

doc.quasar.ai/master

sitewhere1.sitewhere.io/index.html

Developer

Kinetica

Microsoft

Amazon Web Services

quasardb

SiteWhere

Initial release

2012

2015

2021

2009

2010

Current release

7.1, August 2021

2.5.0, January 2023

3.14.1, January 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

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

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.

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Implementation language

C, C++

Java

C++

Java

Server operating systems

Linux

hosted

All OS with a Java VM

BSD
Linux
OS X
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

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

yes

All search fields are automatically indexed

yes

with tags

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

RESTful HTTP API

Java API
RESTful HTTP/JSON API

HTTP API

HTTP REST

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

C#
Java
JavaScript
Python

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

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

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

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

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

consistent hashing

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Implicit feature of the cloud service

yes

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

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate Consistency

Foreign keys

Referential integrity

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

by using LevelDB

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

Transient mode

User concepts

Access control

Access rights for users and roles on table level

yes

using Azure authentication

Cryptographically strong user authentication and audit trail

Users with fine-grained authorization concept

More information provided by the system vendor

Specific characteristics

OpenSearch is a highly scalable and extensible open-source software suite for search,...
» more

Competitive advantages

Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
» more

Typical application scenarios

The OpenSearch platform is used across a broad range of search , analytics, and observability...
» more

Licensing and pricing models

The OpenSearch Project offers open source software licensed under Apache License...
» more

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