DBMS > Adabas vs. Bangdb vs. Blueflood vs. EsgynDB vs. RDF4J

System Properties Comparison Adabas vs. Bangdb vs. Blueflood vs. EsgynDB 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

Converged and high performance database for device data, events, time series, document and graph

Scalable TimeSeries DBMS based on Cassandra

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

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

Primary database model

Multivalue DBMS

Document store
Graph DBMS
Time Series DBMS

Time Series DBMS

Relational DBMS

RDF store

Secondary database models

Spatial DBMS

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

Score	2.79
Rank	#102	Overall
	#2	Multivalue DBMS

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Website

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

Technical documentation

docs.bangdb.com

github.com/rax-maas/blueflood/wiki

rdf4j.org/documentation

Developer

Software AG

Sachin Sinha, BangDB

Rackspace

Esgyn

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

Initial release

1971

2012

2013

2015

2004

Current release

BangDB 2.0, October 2021

License

Commercial or Open Source

commercial

Open Source

BSD 3

Open Source

Apache 2.0

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

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, C++

Java

C++, Java

Java

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux

Linux
OS X

Linux

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

predefined scheme

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

yes: string, long, double, int, geospatial, stream, events

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

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

SQL like support with command line tool

yes

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

Proprietary protocol
RESTful HTTP API

HTTP REST

ADO.NET
JDBC
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

Natural

C
C#
C++
Java
Python

All languages supporting JDBC/ODBC/ADO.Net

Java
PHP
Python

Server-side scripts

Stored procedures

in Natural

Java Stored Procedures

yes

Triggers

yes, Notifications (with Streaming only)

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 (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

based on Cassandra

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

selectable replication factor, Knob for CAP (enterprise version only)

selectable replication factor

based on Cassandra

Multi-source replication between multi datacenters

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable consistency, set CAP knob accordingly

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

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, run db with in-memory only mode

User concepts

Access control

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

yes (enterprise version only)

fine grained access rights according to SQL-standard

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