DBMS > Cubrid vs. Ehcache vs. Faircom EDGE vs. GigaSpaces vs. JaguarDB

System Properties Comparison Cubrid vs. Ehcache vs. Faircom EDGE vs. GigaSpaces vs. JaguarDB

Editorial information provided by DB-Engines

Name

Description

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

A widely adopted Java cache with tiered storage options

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

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Performant, highly scalable DBMS for AI and IoT applications

Primary database model

Relational DBMS

Key-value store

Key-value store
Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Key-value store
Vector DBMS

Secondary database models

Graph DBMS
Search engine

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

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

Score	0.02
Rank	#368	Overall
	#54	Key-value stores
	#156	Relational DBMS

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Website

cubrid.com (korean)
cubrid.org (english)

www.ehcache.org

www.faircom.com/products/faircom-edge

www.gigaspaces.com

www.jaguardb.com

Technical documentation

cubrid.org/manuals

www.ehcache.org/documentation

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

docs.gigaspaces.com/latest/landing.html

www.jaguardb.com/support.html

Developer

CUBRID Corporation, CUBRID Foundation

Terracotta Inc, owned by Software AG

FairCom Corporation

Gigaspaces Technologies

DataJaguar, Inc.

Initial release

2008

2009

1979

2000

2015

Current release

11.0, January 2021

3.10.0, March 2022

V3, October 2020

15.5, September 2020

3.3 July 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2; commercial licenses available

commercial

Restricted, free version available

Open Source

Apache Version 2; Commercial licenses available

Open Source

GPL V3.0

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

C, C++, Java

Java

ANSI C, C++

Java, C++, .Net

C++

the server part. Clients available in other languages

Server operating systems

Linux
Windows

All OS with a Java VM

Android
Linux

ARM, x86
Raspbian
Windows

Linux
macOS
Solaris
Windows

Linux

Data scheme

yes

schema-free

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

schema-free

yes

Typing

predefined data types such as float or date

yes

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

XML can be used for describing objects metadata

Secondary indexes

yes

SQL

Support of SQL

yes

ANSI SQL queries

SQL-99 for query and DML statements

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

JCache

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

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Java

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

.Net
C++
Java
Python
Scala

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

Java Stored Procedures

yes

.Net, JavaScript, C/C++

yes

Triggers

yes

Cache Event Listeners

yes

yes, event driven architecture

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

by using Terracotta Server

File partitioning

Customizable business rules for partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

by using Terracotta Server

yes

Synchronous and asynchronous realtime replication based on transaction logs

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency
Tunable Consistency

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Eventual Consistency

Foreign keys

Referential integrity

yes

when using SQL

Transaction concepts

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

ACID

yes

supports JTA and can work as an XA resource

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

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

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

Role-based access control

rights management via user accounts

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