DBMS > 4D vs. Datomic vs. EJDB vs. Faircom DB

System Properties Comparison 4D vs. Datomic vs. EJDB vs. Faircom DB

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Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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

Primary database model

Relational DBMS

Document store

Key-value store
Relational DBMS

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

Score	2.47
Rank	#110	Overall
	#54	Relational DBMS

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	0.29
Rank	#304	Overall
	#43	Key-value stores
	#136	Relational DBMS

Website

www.4d.com

www.datomic.com

github.com/Softmotions/ejdb

www.faircom.com/products/faircom-db

Technical documentation

developer.4d.com

docs.datomic.com

github.com/Softmotions/ejdb/blob/master/README.md

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

Developer

4D, Inc

Cognitect

Softmotions

FairCom Corporation

Initial release

1984

2012

1979

Current release

v20, April 2023

1.0.6735, June 2023

V12, November 2020

License

Commercial or Open Source

commercial

limited edition free

Open Source

GPLv2

commercial

Restricted, free version available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Clojure

ANSI C, C++

Server operating systems

OS X
Windows

All OS with a Java VM

server-less

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

easily portable to other OSs

Data scheme

yes

schema-free

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

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes, ANSI SQL Types, JSON, typed binary structures

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

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

RESTful HTTP API

in-process shared library

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

Supported programming languages

4D proprietary IDE
PHP

Clojure
Java

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

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

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

.Net, JavaScript, C/C++

Triggers

yes

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

But extensive use of caching in the application peers

none

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

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Foreign keys

Referential integrity

yes

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

tunable from ACID to Eventually Consistent

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

recommended only for testing and development

yes

User concepts

Access control

Users and groups

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

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