DBMS > Adabas vs. Fujitsu Enterprise Postgres vs. Microsoft SQL Server vs. Prometheus vs. SAP SQL Anywhere

System Properties Comparison Adabas vs. Fujitsu Enterprise Postgres vs. Microsoft SQL Server vs. Prometheus vs. SAP SQL Anywhere

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

Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.

Microsofts flagship relational DBMS

Open-source Time Series DBMS and monitoring system

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	2.79
Rank	#102	Overall
	#2	Multivalue DBMS

Score	0.37
Rank	#278	Overall
	#128	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Website

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

www.postgresql.fastware.com

www.microsoft.com/en-us/sql-server

prometheus.io

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

www.postgresql.fastware.com/product-manuals

learn.microsoft.com/en-US/sql/sql-server

prometheus.io/docs

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Software AG

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

Microsoft

SAP

formerly Sybase

Initial release

1971

1989

2015

1992

Current release

Fujitsu Enterprise Postgres 14, January 2022

SQL Server 2022, November 2022

17, July 2015

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

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.

yes

Import of XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

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

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

RESTful HTTP/JSON API

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

Natural

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

in Natural

user defined functions

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes, in C/C++, Java, .Net or Perl

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

partitioning by range, list and by hash

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Source-replica replication

yes, but depending on the SQL-Server Edition

yes

by Federation

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

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