DBMS > Adabas vs. Apache IoTDB vs. HyperSQL vs. Infobright vs. RocksDB

System Properties Comparison Adabas vs. Apache IoTDB vs. HyperSQL vs. Infobright vs. RocksDB

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

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	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	1.02
Rank	#192	Overall
	#90	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

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

iotdb.apache.org

hsqldb.org

ignitetech.com/softwarelibrary/infobrightdb

rocksdb.org

Technical documentation

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

hsqldb.org/web/hsqlDocsFrame.html

github.com/facebook/rocksdb/wiki

Developer

Software AG

Apache Software Foundation

Ignite Technologies Inc.; formerly InfoBright Inc.

Facebook, Inc.

Initial release

1971

2018

2001

2005

2013

Current release

1.1.0, April 2023

2.7.2, June 2023

9.2.1, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

based on BSD license

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

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

Embedded (into Java applications) and Client-Server operating modes

Linux
Windows

Linux

Data scheme

yes

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.

Secondary indexes

yes

Knowledge Grid Technology used instead

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

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

JDBC
Native API

HTTP API

JDBC via HTTP
JDBC
ODBC

ADO.NET
JDBC
ODBC

C++ API
Java API

Supported programming languages

Natural

C
C#
C++
Go
Java
Python
Scala

All languages supporting JDBC/ODBC
Java

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

in Natural

yes

Java, SQL

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

horizontal partitioning

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

none

Source-replica replication

yes

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

Transaction concepts

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

ACID

yes

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)

yes

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

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