DBMS > Adabas vs. Amazon Redshift vs. CouchDB vs. Datomic vs. RDF4J

System Properties Comparison Adabas vs. Amazon Redshift vs. CouchDB vs. Datomic vs. RDF4J

Editorial information provided by DB-Engines

Name

Description

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

used typically together with the Natural programming platform

Large scale data warehouse service for use with business intelligence tools

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

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

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

Primary database model

Secondary database models

Spatial DBMS

using the Geocouch extension

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Trend Chart

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

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

aws.amazon.com/redshift

couchdb.apache.org

www.datomic.com

rdf4j.org

Technical documentation

docs.aws.amazon.com/redshift

docs.couchdb.org/en/stable

docs.datomic.com

rdf4j.org/documentation

Developer

Software AG

Amazon (based on PostgreSQL)

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Cognitect

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

Initial release

1971

2012

2005

2012

2004

Current release

3.3.3, December 2023

1.0.6735, June 2023

License

Commercial or Open Source

commercial

Open Source

Apache version 2

commercial

limited edition free

Open Source

Eclipse Distribution License (EDL), v1.0.

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Erlang

Java, Clojure

Java

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

hosted

Android
BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

restricted

yes

via views

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

yes

does not fully support an SQL-standard

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

JDBC
ODBC

RESTful HTTP/JSON API

RESTful HTTP API

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

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

Clojure
Java

Java
PHP
Python

Server-side scripts

Stored procedures

in Natural

user defined functions

in Python

View functions in JavaScript

yes

Transaction Functions

yes

Triggers

yes

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

improved architecture with release 2.0

none

But extensive use of caching in the application peers

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

yes

Multi-source replication
Source-replica replication

none

But extensive use of caching in the application peers

none

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

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

ACID

atomic operations within a single document possible

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

Durability

Support for making data persistent

yes

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

yes

in-memory storage is supported as well

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

User concepts

Access control

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

fine grained access rights according to SQL-standard

Access rights for users can be defined per database

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