DBMS > Faircom EDGE vs. PostgreSQL vs. Trafodion vs. Yanza

System Properties Comparison Faircom EDGE vs. PostgreSQL vs. Trafodion vs. Yanza

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Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

Transactional SQL-on-Hadoop DBMS

Time Series DBMS for IoT Applications

Primary database model

Key-value store
Relational DBMS

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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	636.25
Rank	#4	Overall
	#4	Relational DBMS

Website

www.faircom.com/products/faircom-edge

www.postgresql.org

trafodion.apache.org

yanza.com

Technical documentation

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

www.postgresql.org/docs

trafodion.apache.org/documentation.html

Developer

FairCom Corporation

PostgreSQL Global Development Group

www.postgresql.org/developer

Apache Software Foundation, originally developed by HP

Yanza

Initial release

1979

1989

1989: Postgres, 1996: PostgreSQL

2014

2015

Current release

V3, October 2020

16.3, May 2024

2.3.0, February 2019

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

BSD

Open Source

Apache 2.0

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

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Implementation language

ANSI C, C++

C++, Java

Server operating systems

Android
Linux

ARM, x86
Raspbian
Windows

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

Linux

Windows

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

yes

ANSI SQL queries

yes

standard with numerous extensions

yes

APIs and other access methods

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

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

ADO.NET
JDBC
ODBC

HTTP API

Supported programming languages

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

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

All languages supporting JDBC/ODBC/ADO.Net

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Java Stored Procedures

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

File partitioning

Customizable business rules for partitioning

partitioning by range, list and (since PostgreSQL 11) by hash

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous and asynchronous realtime replication based on transaction logs

Source-replica replication

other methods possible by using 3rd party extensions

yes, via HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

Immediate 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

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.

fine grained access rights according to SQL-standard

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