DBMS > Faircom DB vs. Geode vs. GridGain vs. openGemini vs. STSdb

System Properties Comparison Faircom DB vs. Geode vs. GridGain vs. openGemini vs. STSdb

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

GridGain is an in-memory computing platform, built on Apache Ignite

An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Key-value store
Relational DBMS

Key-value store

Key-value store
Relational DBMS

Time Series DBMS

Key-value store

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	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	0.01
Rank	#375	Overall
	#39	Time Series DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

www.faircom.com/products/faircom-db

geode.apache.org

www.gridgain.com

www.opengemini.org
github.com/openGemini

github.com/STSSoft/STSdb4

Technical documentation

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

geode.apache.org/docs

www.gridgain.com/docs/index.html

docs.opengemini.org/guide

Developer

FairCom Corporation

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

GridGain Systems, Inc.

Huawei and openGemini community

STS Soft SC

Initial release

1979

2002

2007

2022

2011

Current release

V12, November 2020

1.1, February 2017

GridGain 8.5.1

1.1, July 2023

4.0.8, September 2015

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

Open Source

Apache Version 2.0

Open Source

GPLv2, commercial license available

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

Java, C++, .Net

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
OS X
Solaris
Windows

Linux
Windows

Windows

Data scheme

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

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

yes

Integer, Float, Boolean, String

yes

primitive types and user defined types (classes)

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

SQL

Support of SQL

yes, ANSI SQL with proprietary extensions

SQL-like query language (OQL)

ANSI-99 for query and DML statements, subset of DDL

SQL-like query language

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

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

HTTP REST

.NET Client API

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

C#
C++
Java
PHP
Python
Ruby
Scala

C
C++
Go
Java
JavaScript (Node.js)
Python
Rust

C#
Java

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

user defined functions

yes (compute grid and cache interceptors can be used instead)

Triggers

yes

Cache Event Listeners

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

none

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

yes (replicated cache)

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

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

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

Access rights per client and object definable

Security Hooks for custom implementations

Administrators and common users accounts

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