DBMS > 4D vs. Faircom DB vs. GridDB vs. IBM Cloudant

System Properties Comparison 4D vs. Faircom DB vs. GridDB vs. IBM Cloudant

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Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

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

Scalable in-memory time series database optimized for IoT and Big Data

Database as a Service offering based on Apache CouchDB

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Time Series DBMS

Document store

Secondary database models

Key-value store
Relational DBMS

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

Score	2.37
Rank	#110	Overall
	#54	Relational DBMS

Score	0.18
Rank	#314	Overall
	#45	Key-value stores
	#141	Relational DBMS

Score	1.91
Rank	#123	Overall
	#10	Time Series DBMS

Score	2.85
Rank	#95	Overall
	#18	Document stores

Website

www.4d.com

www.faircom.com/products/faircom-db

griddb.net

www.ibm.com/products/cloudant

Technical documentation

developer.4d.com

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

docs.griddb.net

cloud.ibm.com/docs/Cloudant

Developer

4D, Inc

FairCom Corporation

Toshiba Corporation

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Initial release

1984

1979

2013

2010

Current release

v20, April 2023

V13, July 2024

5.1, August 2022

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

ANSI C, C++

C++

Erlang

Server operating systems

OS X
Windows

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

easily portable to other OSs

Linux

hosted

Data scheme

yes

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

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

yes

numerical, string, blob, geometry, boolean, timestamp

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

close to SQL 92

yes, ANSI SQL with proprietary extensions

SQL92, SQL-like TQL (Toshiba Query Language)

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

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

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

RESTful HTTP/JSON API

Supported programming languages

4D proprietary IDE
PHP

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

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

C#
Java
JavaScript
Objective-C
PHP
Ruby

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

View functions (Map-Reduce) in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

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

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Immediate consistency within container, eventual consistency across containers

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

tunable from ACID to Eventually Consistent

ACID at container level

atomic operations within a document possible

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

Durability

Support for making data persistent

yes

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

Users and groups

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

Access rights for users can be defined per database

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More resources

DB-Engines blog posts

MySQL, PostgreSQL and Redis are the winners of the March ranking
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