DBMS > Microsoft Azure Search vs. Quasardb vs. SiteWhere

System Properties Comparison Microsoft Azure Search vs. Quasardb vs. SiteWhere

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Editorial information provided by DB-Engines

Name

Description

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

Distributed, high-performance timeseries database

M2M integration platform for persisting/querying time series data

Primary database model

Search engine

Time Series DBMS

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

Score	7.61
Rank	#58	Overall
	#6	Search engines

Score	0.09
Rank	#321	Overall
	#28	Time Series DBMS

Score	0.00
Rank	#363	Overall
	#34	Time Series DBMS

Website

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

quasardb.net

sitewhere.io

Technical documentation

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

doc.quasar.ai/master

sitewhere.io/docs/2.1.0

Developer

Microsoft

quasardb

SiteWhere

Initial release

2015

2009

2010

Current release

3.13.3, April 2022

License

Commercial or Open Source

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.

Implementation language

C++

Java

Server operating systems

hosted

BSD
Linux
OS X
Windows

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

yes

with tags

SQL

Support of SQL

SQL-like query language

APIs and other access methods

RESTful HTTP API

HTTP API

HTTP REST

Supported programming languages

.Net
C#

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

Server-side scripts

Stored procedures

Triggers

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

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

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

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

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

High-performance , high-speed, fully integrated timeseries database Seamlessly combines...
» more

Competitive advantages

High performance in a cost-effective small package Real-time results for even large...
» more

Typical application scenarios

Tick database Predictive maintenance Pre-deal checks Large scale monitoring
» more

Key customers

Large EU investment banks US based hedge funds Orolia Tellmeplus
» more

Market metrics

Has been running in very demanding production environments since 2013 Rapid adoption...
» more

Licensing and pricing models

Community edition limited to 2 nodes and 16 GiB of storage per node available for...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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