DBMS > Adabas vs. EsgynDB vs. FatDB vs. RDF4J vs. RethinkDB

System Properties Comparison Adabas vs. EsgynDB vs. FatDB vs. RDF4J vs. RethinkDB

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

OLTP - DBMS for mainframes and Linux/Unix/Windows environments

used typically together with the Natural programming platform

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Primary database model

Multivalue DBMS

Relational DBMS

Document store
Key-value store

RDF store

Document store

Secondary database models

Spatial DBMS

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

Score	2.64
Rank	#104	Overall
	#1	Multivalue DBMS

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Score	2.58
Rank	#105	Overall
	#20	Document stores

Website

www.softwareag.com/en_corporate/platform/adabas-natural.html

www.esgyn.cn

rdf4j.org

rethinkdb.com

Technical documentation

rdf4j.org/documentation

rethinkdb.com/docs

Developer

Software AG

Esgyn

FatCloud

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

The Linux Foundation

since July 2017

Initial release

1971

2015

2012

2004

2009

Current release

2.4.1, August 2020

License

Commercial or Open Source

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Apache Version 2

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++, Java

Java

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux

Windows

Linux
OS X
Unix
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

RDF Schemas

schema-free

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

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.

Secondary indexes

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

yes

Via inetgration in SQL Server

APIs and other access methods

HTTP API

with add-on software Adabas SOA Gateway
SOAP-based API

with add-on software Adabas SOA Gateway

ADO.NET
JDBC
ODBC

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

Natural

All languages supporting JDBC/ODBC/ADO.Net

Java
PHP
Python

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Server-side scripts

Stored procedures

in Natural

Java Stored Procedures

yes

via applications

yes

Triggers

yes

via applications

yes

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

yes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas Vista

Sharding

none

Sharding

range based

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Multi-source replication between multi datacenters

selectable replication factor

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

Atomic single-document operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

In-memory capabilities

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

User concepts

Access control

only with OS-specific tools (e.g. IBM RACF, CA Top Secret)

fine grained access rights according to SQL-standard

Can implement custom security layer via applications

yes

users and table-level permissions

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More resources

DB-Engines blog posts

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