DBMS > Faircom DB vs. Greenplum vs. openGauss

System Properties Comparison Faircom DB vs. Greenplum vs. openGauss

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Editorial information provided by DB-Engines

Name

Description

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

Primary database model

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.20
Rank	#318	Overall
	#48	Key-value stores
	#141	Relational DBMS

Score	8.37
Rank	#48	Overall
	#30	Relational DBMS

Score	1.08
Rank	#183	Overall
	#84	Relational DBMS

Website

www.faircom.com/products/faircom-db

greenplum.org

gitee.com/opengauss
opengauss.org

Technical documentation

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

docs.greenplum.org

docs.opengauss.org/en
gitee.com/opengauss/docs

Developer

FairCom Corporation

Pivotal Software Inc.

Huawei and openGauss community

Initial release

1979

2005

2019

Current release

V12, November 2020

7.0.0, September 2023

3.0, March 2022

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Apache 2.0

Open Source

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++

C, C++, Java

Server operating systems

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

Linux

Data scheme

schema free, schema optional, schema required, partial schema,

yes

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

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

since Version 4.2

Secondary indexes

yes

SQL

Support of SQL

yes, ANSI SQL with proprietary extensions

yes

ANSI SQL 2011

APIs and other access methods

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

JDBC
ODBC

Supported programming languages

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

C
Java
Perl
Python
R

C
C++
Java

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

horizontal partitioning (by range, list and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

tunable from ACID to Eventually Consistent

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Yes, tunable from durable to delayed durability to in-memory

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 with additional protections for files

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

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More resources

Recent citations in the news

FairCom kicks off new era of database technology USA - English
10 November 2020, PR Newswire

provided by Google News

VMware Greenplum on AWS: Parallel Postgres for Enterprise Analytics at Scale | Amazon Web Services
9 September 2019, AWS Blog

1. Introducing the Greenplum Database - Data Warehousing with Greenplum [Book]
6 December 2018, oreilly.com

RSA: EMC integrates Hadoop with Greenplum database
26 February 2013, DatacenterDynamics

Greenplum 6 ventures outside the analytic box | ZDNET
19 March 2019, ZDNet

Greenplum 6 review: Jack of all trades, master of some
7 November 2019, InfoWorld

provided by Google News

openGauss Open Source Community Officially Launch
1 July 2020, Huawei

The openGauss powers database industry forward through innovation
6 January 2022, Global Times

Huawei's Four Open Source Basic Software Projects Infuse Diversified Computing Power into Every Line of Code
12 October 2020, PR Newswire

About HUAWEI Open Source
9 February 2022, Huawei

provided by Google News

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