DBMS > Cubrid vs. Faircom EDGE vs. PouchDB vs. searchxml

System Properties Comparison Cubrid vs. Faircom EDGE vs. PouchDB vs. searchxml

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Editorial information provided by DB-Engines

Name

Description

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

JavaScript DBMS with an API inspired by CouchDB

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Document store

Native XML DBMS
Search engine

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

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	0.02
Rank	#368	Overall
	#54	Key-value stores
	#156	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Website

cubrid.com (korean)
cubrid.org (english)

www.faircom.com/products/faircom-edge

pouchdb.com

www.searchxml.net/category/products

Technical documentation

cubrid.org/manuals

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

pouchdb.com/guides

www.searchxml.net/support/handouts

Developer

CUBRID Corporation, CUBRID Foundation

FairCom Corporation

Apache Software Foundation

informationpartners gmbh

Initial release

2008

1979

2012

2015

Current release

11.0, January 2021

V3, October 2020

7.1.1, June 2019

1.0

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Restricted, free version available

Open Source

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++, Java

ANSI C, C++

JavaScript

C++

Server operating systems

Linux
Windows

Android
Linux

ARM, x86
Raspbian
Windows

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

Windows

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

schema-free

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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.

yes

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

ANSI SQL queries

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

HTTP REST

only for PouchDB Server
JavaScript API

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

JavaScript

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

Java Stored Procedures

yes

.Net, JavaScript, C/C++

View functions in JavaScript

yes

on the application server

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

File partitioning

Customizable business rules for partitioning

Sharding

with a proxy-based framework, named couchdb-lounge

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Synchronous and asynchronous realtime replication based on transaction logs

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency
Tunable Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

Domain, group and role-based access control at the document level and for application services

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More resources

DB-Engines blog posts

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