DBMS > Faircom EDGE vs. PouchDB vs. XTDB vs. YottaDB

System Properties Comparison Faircom EDGE vs. PouchDB vs. XTDB vs. YottaDB

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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

JavaScript DBMS with an API inspired by CouchDB

A general purpose database with bitemporal SQL and Datalog and graph queries

A fast and solid embedded Key-value store

Primary database model

Key-value store
Relational DBMS

Document store

Key-value store

Secondary database models

Relational DBMS

using the Octo plugin

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

Score	0.09
Rank	#362	Overall
	#53	Key-value stores
	#155	Relational DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	0.18
Rank	#332	Overall
	#46	Document stores

Score	0.28
Rank	#306	Overall
	#44	Key-value stores

Website

www.faircom.com/products/faircom-edge

pouchdb.com

github.com/xtdb/xtdb
www.xtdb.com

yottadb.com

Technical documentation

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

pouchdb.com/guides

www.xtdb.com/docs

yottadb.com/resources/documentation

Developer

FairCom Corporation

Apache Software Foundation

Juxt Ltd.

YottaDB, LLC

Initial release

1979

2012

2019

2001

Current release

V3, October 2020

7.1.1, June 2019

1.19, September 2021

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

MIT License

Open Source

AGPL 3.0

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

ANSI C, C++

JavaScript

Clojure

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

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

All OS with a Java 8 (and higher) VM
Linux

Docker
Linux

Data scheme

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

schema-free

Typing

predefined data types such as float or date

yes, ANSI Standard SQL Types

yes, extensible-data-notation format

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

limited SQL, making use of Apache Calcite

by using the Octo plugin

APIs and other access methods

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

HTTP REST
JDBC

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

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

JavaScript

Clojure
Java

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

View functions in JavaScript

Triggers

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

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, each node contains all data

yes

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

Eventual Consistency

Foreign keys

Referential integrity

yes

when using SQL

Transaction concepts

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

ACID

optimistic locking

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, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

Users and groups based on OS-security mechanisms

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More resources

DB-Engines blog posts

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