DBMS > Adabas vs. Amazon Aurora vs. Hawkular Metrics vs. Microsoft Azure Table Storage vs. Microsoft SQL Server

System Properties Comparison Adabas vs. Amazon Aurora vs. Hawkular Metrics vs. Microsoft Azure Table Storage vs. Microsoft SQL Server

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

MySQL and PostgreSQL compatible cloud service by Amazon

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

A Wide Column Store for rapid development using massive semi-structured datasets

Microsofts flagship relational DBMS

Primary database model

Secondary database models

Document store

Document store
Graph DBMS
Spatial DBMS

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

Score	3.58
Rank	#91	Overall
	#1	Multivalue DBMS

Score	8.50
Rank	#49	Overall
	#31	Relational DBMS

Score	0.04
Rank	#374	Overall
	#38	Time Series DBMS

Score	4.92
Rank	#73	Overall
	#6	Wide column stores

Score	829.80
Rank	#3	Overall
	#3	Relational DBMS

Website

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

aws.amazon.com/rds/aurora

www.hawkular.org

azure.microsoft.com/en-us/services/storage/tables

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

Technical documentation

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html

www.hawkular.org/hawkular-metrics/docs/user-guide

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

Developer

Software AG

Amazon

Community supported by Red Hat

Microsoft

Initial release

1971

2015

2014

2012

1989

Current release

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

restricted free version is available

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

Java

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

hosted

Linux
OS X
Windows

hosted

Linux
Windows

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

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
ODBC

HTTP REST

RESTful HTTP API

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

Supported programming languages

Natural

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Go
Java
Python
Ruby

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

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

Server-side scripts

Stored procedures

in Natural

yes

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

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

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

horizontal partitioning

Sharding

based on Cassandra

Sharding

Implicit feature of the cloud service

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Source-replica replication

selectable replication factor

based on Cassandra

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking

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

Access rights based on private key authentication or shared access signatures

fine grained access rights according to SQL-standard

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