DBMS > Adabas vs. Datomic vs. RDF4J vs. Transwarp Hippo

System Properties Comparison Adabas vs. Datomic vs. RDF4J vs. Transwarp Hippo

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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

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.

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.00
Rank	#383	Overall
	#13	Vector DBMS

Website

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

www.datomic.com

rdf4j.org

www.transwarp.cn/en/subproduct/hippo

Technical documentation

docs.datomic.com

rdf4j.org/documentation

Developer

Software AG

Cognitect

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

Initial release

1971

2012

2004

2023

Current release

1.0.6735, June 2023

1.0, May 2023

License

Commercial or Open Source

commercial

limited edition free

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

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

Java, Clojure

Java

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

All OS with a Java VM

Linux
OS X
Unix
Windows

Linux
macOS

Data scheme

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

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

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

RESTful HTTP API

Supported programming languages

Natural

Clojure
Java

Java
PHP
Python

C++
Java
Python

Server-side scripts

Stored procedures

in Natural

yes

Transaction Functions

yes

Triggers

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

none

But extensive use of caching in the application peers

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

none

But extensive use of caching in the application peers

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

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

yes

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

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

Role based access control and fine grained access rights

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