DBMS > Faircom EDGE vs. Kinetica vs. PouchDB

System Properties Comparison Faircom EDGE vs. Kinetica vs. PouchDB

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Editorial information provided by DB-Engines

Name

Description

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

Fully vectorized database across both GPUs and CPUs

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Key-value store
Relational DBMS

Relational DBMS

Document store

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	0.02
Rank	#364	Overall
	#55	Key-value stores
	#153	Relational DBMS

Score	0.41
Rank	#254	Overall
	#118	Relational DBMS

Score	1.94
Rank	#120	Overall
	#21	Document stores

Website

www.faircom.com/products/faircom-edge

www.kinetica.com

pouchdb.com

Technical documentation

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

docs.kinetica.com

pouchdb.com/guides

Developer

FairCom Corporation

Kinetica

Apache Software Foundation

Initial release

1979

2012

Current release

V3, October 2020

7.1, August 2021

7.1.1, June 2019

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

Open Source

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

ANSI C, C++

C, C++

JavaScript

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

Linux

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

Data scheme

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

yes

schema-free

Typing

predefined data types such as float or date

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

SQL

Support of SQL

yes

ANSI SQL queries

SQL-like DML and DDL statements

APIs and other access methods

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

JDBC
ODBC
RESTful HTTP API

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

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

C++
Java
JavaScript (Node.js)
Python

JavaScript

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

user defined functions

View functions in JavaScript

Triggers

yes

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

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

Source-replica replication

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

Foreign keys

Referential integrity

yes

when using SQL

yes

Transaction concepts

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

ACID

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

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

User concepts

Access control

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

Access rights for users and roles on table level

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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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