DBMS > Adabas vs. Kinetica vs. MaxDB vs. Microsoft SQL Server vs. OrientDB

System Properties Comparison Adabas vs. Kinetica vs. MaxDB vs. Microsoft SQL Server vs. OrientDB

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

Fully vectorized database across both GPUs and CPUs

A robust and reliable RDBMS optimized to run all major SAP solutions

Microsofts flagship relational DBMS

Multi-model DBMS (Document, Graph, Key/Value)

Primary database model

Multivalue DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	2.64
Rank	#104	Overall
	#1	Multivalue DBMS

Score	0.42
Rank	#261	Overall
	#120	Relational DBMS

Score	2.15
Rank	#115	Overall
	#55	Relational DBMS

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	3.02
Rank	#88	Overall
	#16	Document stores
	#6	Graph DBMS
	#12	Key-value stores

Website

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

www.kinetica.com

maxdb.sap.com

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

orientdb.org

Technical documentation

docs.kinetica.com

maxdb.sap.com/documentation

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

www.orientdb.com/docs/last/index.html

Developer

Software AG

Kinetica

SAP, acquired from Software AG (Adabas-D) in 1997

Microsoft

OrientDB LTD; CallidusCloud; SAP

Initial release

1971

2012

1984

1989

2010

Current release

7.1, August 2021

7.9.10.12, February 2024

SQL Server 2022, November 2022

3.2.29, March 2024

License

Commercial or Open Source

commercial

Limited community edition free

commercial

restricted free version is available

Open Source

Apache version 2

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

C++

Java

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux

AIX
HP-UX
Linux
Solaris
Windows

Linux
Windows

All OS with a Java JDK (>= JDK 6)

Data scheme

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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

Secondary indexes

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

SQL-like DML and DDL statements

yes

SQL-like query language, no joins

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
WebDAV

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

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

Supported programming languages

Natural

C++
Java
JavaScript (Node.js)
Python

.Net
C#
Java
Perl
PHP
Python

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

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

in Natural

user defined functions

yes

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

Java, Javascript

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Hooks

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

none

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

Sharding

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

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

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

GPU vRAM or System RAM

yes

User concepts

Access control

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

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

Access rights for users and roles; record level security configurable

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