DBMS > Adabas vs. Microsoft SQL Server vs. Oracle Berkeley DB vs. SAP IQ vs. Trafodion

System Properties Comparison Adabas vs. Microsoft SQL Server vs. Oracle Berkeley DB vs. SAP IQ vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

OLTP - DBMS for mainframes and Linux/Unix/Windows environments

used typically together with the Natural programming platform

Microsofts flagship relational DBMS

Widely used in-process key-value store

Columnar RDBMS optimized for Big Data analytics

Transactional SQL-on-Hadoop DBMS

Primary database model

Multivalue DBMS

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Relational DBMS

column-oriented

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Website

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

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

www.oracle.com/database/technologies/related/berkeleydb.html

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

trafodion.apache.org

Technical documentation

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

docs.oracle.com/cd/E17076_05/html/index.html

help.sap.com/docs/SAP_IQ

trafodion.apache.org/documentation.html

Developer

Software AG

Microsoft

Oracle

originally developed by Sleepycat, which was acquired by Oracle

SAP, formerly Sybase

Apache Software Foundation, originally developed by HP

Initial release

1971

1989

1994

2014

Current release

SQL Server 2022, November 2022

18.1.40, May 2020

16.1 SPS04, April 2019

2.3.0, February 2019

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

commercial license available

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

C++

C, Java, C++ (depending on the Berkeley DB edition)

C++, Java

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

AIX
HP-UX
Linux
Solaris
Windows

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

yes

SQL interfaced based on SQLite is available

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
ODBC
OLE DB
Tabular Data Stream (TDS)

ADO.NET
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

Natural

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

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

C
C#
C++
Java
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

in Natural

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

yes

Java Stored Procedures

Triggers

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

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

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

none

shared disk or shared nothing architectures with SAP IQ Multiplexer

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

yes, but depending on the SQL-Server Edition

Source-replica replication

SAP/Sybase Replication Server

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

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

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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