DBMS > Adabas vs. BaseX vs. FatDB vs. Graphite

System Properties Comparison Adabas vs. BaseX vs. FatDB vs. Graphite

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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

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

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

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Primary database model

Multivalue DBMS

Native XML DBMS

Document store
Key-value store

Time Series DBMS

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	1.73
Rank	#142	Overall
	#4	Native XML DBMS

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Website

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

basex.org

github.com/graphite-project/graphite-web

Technical documentation

docs.basex.org

graphite.readthedocs.io

Developer

Software AG

BaseX GmbH

FatCloud

Chris Davis

Initial release

1971

2007

2012

2006

Current release

10.7, August 2023

License

Commercial or Open Source

commercial

Open Source

BSD license

commercial

Open Source

Apache 2.0

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

Java

Python

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux
OS X
Windows

Windows

Linux
Unix

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

XQuery supports types

yes

Numeric data only

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

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

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

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

HTTP API
Sockets

Supported programming languages

Natural

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

in Natural

yes

via applications

Triggers

yes

via events

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

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

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

none

selectable replication factor

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

none

Foreign keys

Referential integrity

Transaction concepts

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

ACID

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes

locking

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.

User concepts

Access control

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

Users with fine-grained authorization concept on 4 levels

Can implement custom security layer via applications

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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

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