DBMS > Adabas vs. Amazon Aurora vs. Microsoft SQL Server vs. PieCloudDB vs. RRDtool

System Properties Comparison Adabas vs. Amazon Aurora vs. Microsoft SQL Server vs. PieCloudDB vs. RRDtool

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

Microsofts flagship relational DBMS

A cloud-native analytic database platform with new technologoy for elastic MPP

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Primary database model

Multivalue DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Document store

Document store
Graph DBMS
Spatial DBMS

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	7.91
Rank	#50	Overall
	#32	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.25
Rank	#304	Overall
	#138	Relational DBMS

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Website

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

aws.amazon.com/rds/aurora

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

www.openpie.com

oss.oetiker.ch/rrdtool

Technical documentation

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

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

oss.oetiker.ch/rrdtool/doc

Developer

Software AG

Amazon

Microsoft

OpenPie

Tobias Oetiker

Initial release

1971

2015

1989

1999

Current release

SQL Server 2022, November 2022

2.1, January 2023

1.8.0, 2022

License

Commercial or Open Source

commercial

restricted free version is available

commercial

Open Source

GPL V2 and FLOSS

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

hosted

Linux
Windows

hosted

HP-UX
Linux

Data scheme

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

Exporting into and restoring from XML files possible

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

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

CLI Client
JDBC
ODBC

in-process shared library
Pipes

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

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

Java
PL/SQL
Python
R

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Server-side scripts

Stored procedures

in Natural

yes

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

user defined functions

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

horizontal partitioning

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

yes

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

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

by using the rrdcached daemon

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

User Roles and pluggable authentication with full SQL Standard

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

Sail-Cloud China Shipbuilding Group Haizhou System Soochow Securities etc.,
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Licensing and pricing models

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