DBMS > Adabas vs. mSQL vs. openGemini vs. Spark SQL

System Properties Comparison Adabas vs. mSQL vs. openGemini vs. Spark SQL

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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

mSQL (Mini SQL) is a simple and lightweight RDBMS

An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

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

Score	2.79
Rank	#102	Overall
	#2	Multivalue DBMS

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	0.09
Rank	#361	Overall
	#37	Time Series DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Website

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

hughestech.com.au/products/msql

www.opengemini.org
github.com/openGemini

spark.apache.org/sql

Technical documentation

docs.opengemini.org/guide

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Software AG

Hughes Technologies

Huawei and openGemini community

Apache Software Foundation

Initial release

1971

1994

2022

2014

Current release

4.4, October 2021

1.1, July 2023

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

free licenses can be provided

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Scala

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Integer, Float, Boolean, String

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.

Secondary indexes

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

SQL-like query language

SQL-like DML and DDL statements

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

HTTP REST

JDBC
ODBC

Supported programming languages

Natural

C
C++
Delphi
Java
Perl
PHP
Tcl

C
C++
Go
Java
JavaScript (Node.js)
Python
Rust

Java
Python
R
Scala

Server-side scripts

Stored procedures

in Natural

Triggers

Partitioning methods

Methods for storing different data on different nodes

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

none

Sharding

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

none

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

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)

Administrators and common users accounts

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