DBMS > Linter vs. PouchDB vs. Quasardb vs. SiteWhere

System Properties Comparison Linter vs. PouchDB vs. Quasardb vs. SiteWhere

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Editorial information provided by DB-Engines

Name

Description

RDBMS for high security requirements

JavaScript DBMS with an API inspired by CouchDB

Distributed, high-performance timeseries database

M2M integration platform for persisting/querying time series data

Primary database model

Relational DBMS

Document store

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	0.03
Rank	#368	Overall
	#156	Relational DBMS

Score	2.18
Rank	#114	Overall
	#21	Document stores

Score	0.13
Rank	#332	Overall
	#28	Time Series DBMS

Score	0.07
Rank	#347	Overall
	#33	Time Series DBMS

Website

linter.ru

pouchdb.com

quasar.ai

github.com/sitewhere/sitewhere

Technical documentation

pouchdb.com/guides

doc.quasar.ai/master

sitewhere1.sitewhere.io/index.html

Developer

relex.ru

Apache Software Foundation

quasardb

SiteWhere

Initial release

1990

2012

2009

2010

Current release

7.1.1, June 2019

3.14.1, January 2024

License

Commercial or Open Source

commercial

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

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C and C++

JavaScript

C++

Java

Server operating systems

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

server-less, requires a JavaScript environment (browser, Node.js)

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

via views

yes

with tags

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

HTTP REST

only for PouchDB Server
JavaScript API

HTTP API

HTTP REST

Supported programming languages

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

JavaScript

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

Server-side scripts

Stored procedures

yes

proprietary syntax with the possibility to convert from PL/SQL

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

with a proxy-based framework, named couchdb-lounge

Sharding

consistent hashing

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

Source-replica replication with selectable replication factor

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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 IndexedDB, WebSQL or LevelDB as backend

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

Cryptographically strong user authentication and audit trail

Users with fine-grained authorization concept

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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