DBMS > Adabas vs. Graphite vs. Infobright vs. OushuDB

System Properties Comparison Adabas vs. Graphite vs. Infobright vs. OushuDB

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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

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

Primary database model

Multivalue DBMS

Time Series DBMS

Relational DBMS

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	0.04
Rank	#363	Overall
	#154	Relational DBMS

Website

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

github.com/graphite-project/graphite-web

ignitetech.com/softwarelibrary/infobrightdb

www.oushu.com/product/oushuDB

Technical documentation

graphite.readthedocs.io

www.oushu.com/documentation

Developer

Software AG

Chris Davis

Ignite Technologies Inc.; formerly InfoBright Inc.

Oushu

Initial release

1971

2006

2005

Current release

4.0.1, August 2020

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

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

Python

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux
Unix

Linux
Windows

Linux

Data scheme

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

yes

Full-featured ANSI SQL support

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

HTTP API
Sockets

ADO.NET
JDBC
ODBC

JDBC
ODBC

Supported programming languages

Natural

JavaScript (Node.js)
Python

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C++

Server-side scripts

Stored procedures

in Natural

yes

Triggers

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

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

locking

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

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

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

Kerberos, SSL and role based access

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

show all

Recent citations in the news

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