DBMS > Faircom DB vs. Geode vs. Postgres-XL vs. Tibero

System Properties Comparison Faircom DB vs. Geode vs. Postgres-XL vs. Tibero

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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.

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Key-value store
Relational DBMS

Key-value store

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	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	1.78
Rank	#140	Overall
	#64	Relational DBMS

Website

www.faircom.com/products/faircom-db

geode.apache.org

www.postgres-xl.org

us.tmaxsoft.com/products/tibero

Technical documentation

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

geode.apache.org/docs

www.postgres-xl.org/documentation

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

FairCom Corporation

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

TmaxSoft

Initial release

1979

2002

2014

since 2012, originally named StormDB

2003

Current release

V12, November 2020

1.1, February 2017

10 R1, October 2018

6, April 2015

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

Mozilla public license

commercial

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++

Java

C and Assembler

Server operating systems

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

easily portable to other OSs

All OS with a Java VM

the JDK (8 or later) is also required

Linux
macOS

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

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

schema-free

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

XML type, but no XML query functionality

yes

Secondary indexes

yes

SQL

Support of SQL

yes, ANSI SQL with proprietary extensions

SQL-like query language (OQL)

yes

distributed, parallel query execution

yes

APIs and other access methods

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

Java Client API
Memcached protocol
RESTful HTTP API

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

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

.Net
All JVM based languages
C++
Groovy
Java
Scala

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

user defined functions

Persistent Stored Procedure (PSM)

Triggers

yes

Cache Event Listeners

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, hash, list or composite

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).

Multi-source replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

Eventual Consistency

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

yes, on a single node

ACID

MVCC

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

planned for next version

User concepts

Access control

Fine grained access rights according to SQL-standard with additional protections for files

Access rights per client and object definable

fine grained access rights according to SQL-standard

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

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