DBMS > Adabas vs. Apache IoTDB vs. RethinkDB vs. SAP HANA

System Properties Comparison Adabas vs. Apache IoTDB vs. RethinkDB vs. SAP HANA

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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

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

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Secondary database models

Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	2.64
Rank	#104	Overall
	#1	Multivalue DBMS

Score	1.31
Rank	#159	Overall
	#14	Time Series DBMS

Score	2.58
Rank	#105	Overall
	#20	Document stores

Score	41.32
Rank	#23	Overall
	#16	Relational DBMS

Website

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

iotdb.apache.org

rethinkdb.com

www.sap.com/products/hana.html

Technical documentation

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

rethinkdb.com/docs

help.sap.com/hana

Developer

Software AG

Apache Software Foundation

The Linux Foundation

since July 2017

SAP

Initial release

1971

2018

2009

2010

Current release

1.1.0, April 2023

2.4.1, August 2020

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

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

All OS with a Java VM (>= 1.8)

Linux
OS X
Windows

Appliance or cloud-service

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

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

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

JDBC
ODBC

Supported programming languages

Natural

C
C#
C++
Go
Java
Python
Scala

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Server-side scripts

Stored procedures

in Natural

yes

SQLScript, R

Triggers

yes

Client-side triggers through changefeeds

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)

Sharding

range based

yes

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

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

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

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

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

users and table-level permissions

yes

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