DBMS > Adabas vs. Apache IoTDB vs. H2 vs. MariaDB vs. SWC-DB

System Properties Comparison Adabas vs. Apache IoTDB vs. H2 vs. MariaDB vs. SWC-DB

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

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

MySQL application compatible open source RDBMS, enhanced with high availability, security, interoperability and performance capabilities. MariaDB ColumnStore provides a column-oriented storage engine and MariaDB Xpand supports distributed SQL.

A high performance, scalable Wide Column DBMS

Primary database model

Secondary database models

Spatial DBMS

Document store
Graph DBMS

with OQGraph storage engine
Spatial DBMS

Time Series DBMS

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	93.21
Rank	#13	Overall
	#9	Relational DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

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

iotdb.apache.org

www.h2database.com

mariadb.com

Site of MariaDB Corporation
mariadb.org

Site of MariaDB Foundation

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

www.h2database.com/html/main.html

mariadb.com/kb/en/library

Developer

Software AG

Apache Software Foundation

Thomas Mueller

MariaDB Corporation Ab (MariaDB Enterprise),
MariaDB Foundation (community MariaDB Server)

The lead developer Monty Widenius is the original author of MySQL

Alex Kashirin

Initial release

1971

2018

2005

2009

Fork of MySQL, which was first released in 1995

2020

Current release

1.1.0, April 2023

2.2.220, July 2023

11.3.2, February 2024

0.5, April 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

GPL version 2, commercial enterprise subscription available

Open Source

GPL V3

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

Java

C and C++

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

All OS with a Java VM (>= 1.8)

All OS with a Java VM

FreeBSD
Linux
Solaris
Windows

ColumnStore storage engine not available on Windows

Linux

Data scheme

yes

Dynamic columns are supported

schema-free

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 query language

yes

with proprietary extensions

SQL-like query language

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
Native API

JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Proprietary protocol
Thrift

Supported programming languages

Natural

C
C#
C++
Go
Java
Python
Scala

Java

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

C++

Server-side scripts

Stored procedures

in Natural

yes

Java Stored Procedures and User-Defined Functions

yes

PL/SQL compatibility added with version 10.3

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 (by time range) + vertical partitioning (by deviceId)

none

several options for horizontal partitioning and Sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

With clustering: 2 database servers on different computers operate on identical copies of a database

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

not for in-memory storage engine

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

with MEMORY storage engine

User concepts

Access control

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

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

Web, SaaS and Cloud operational applications that require high availability, scalability...
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Key customers

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Market metrics

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Licensing and pricing models

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