DBMS > Adabas vs. EXASOL vs. Kinetica vs. Microsoft Azure Cosmos DB vs. SAP SQL Anywhere

System Properties Comparison Adabas vs. EXASOL vs. Kinetica vs. Microsoft Azure Cosmos DB 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

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Fully vectorized database across both GPUs and CPUs

Globally distributed, horizontally scalable, multi-model database service

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

Primary database model

Multivalue DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Spatial DBMS
Time Series 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	1.76
Rank	#139	Overall
	#62	Relational DBMS

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Website

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

www.exasol.com

www.kinetica.com

azure.microsoft.com/services/cosmos-db

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

Technical documentation

www.exasol.com/resources

docs.kinetica.com

learn.microsoft.com/azure/cosmos-db

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Software AG

Exasol

Kinetica

Microsoft

SAP

formerly Sybase

Initial release

1971

2000

2012

2014

1992

Current release

7.1, August 2021

17, July 2015

License

Commercial or Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

yes

SQL-like DML and DDL statements

SQL-like query language

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

.Net
JDBC
ODBC
WebSocket

JDBC
ODBC
RESTful HTTP API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

Natural

Java
Lua
Python
R

C++
Java
JavaScript (Node.js)
Python

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

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

Server-side scripts

Stored procedures

in Natural

user defined functions

JavaScript

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

Triggers

yes

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

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Source-replica replication

yes

Implicit feature of the cloud service

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

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, groups and roles according to SQL-standard

Access rights for users and roles on table level

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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