DBMS > Adabas vs. Altibase vs. Amazon Redshift vs. Ignite vs. Riak TS

System Properties Comparison Adabas vs. Altibase vs. Amazon Redshift vs. Ignite vs. Riak TS

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 enterprise grade, high-performance RDBMS

Large scale data warehouse service for use with business intelligence tools

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Multivalue DBMS

Relational DBMS

Key-value store
Relational DBMS

Time Series DBMS

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

Score	3.58
Rank	#91	Overall
	#1	Multivalue DBMS

Score	1.00
Rank	#194	Overall
	#91	Relational DBMS

Score	19.03
Rank	#34	Overall
	#21	Relational DBMS

Score	3.64
Rank	#89	Overall
	#13	Key-value stores
	#48	Relational DBMS

Score	0.25
Rank	#308	Overall
	#26	Time Series DBMS

Website

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

altibase.com

aws.amazon.com/redshift

ignite.apache.org

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

docs.aws.amazon.com/redshift

apacheignite.readme.io/docs

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Software AG

Altibase

Amazon (based on PostgreSQL)

Apache Software Foundation

Open Source, formerly Basho Technologies

Initial release

1971

1999

2012

2015

Current release

v7.3, 2023, August 2023

Apache Ignite 2.6

3.0.0, September 2022

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

commercial

Open Source

Apache 2.0

Open Source

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++

C++, Java, .Net

Erlang

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

AIX
HP-UX
Linux

hosted

Linux
OS X
Solaris
Windows

Linux
OS X

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.

yes

Secondary indexes

yes

restricted

yes

restricted

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

ANSI SQL-92

yes

does not fully support an SQL-standard

ANSI-99 for query and DML statements, subset of DDL

yes, limited

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
Proprietary protocol

JDBC
ODBC

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

HTTP API
Native Erlang Interface

Supported programming languages

Natural

C
C++
Java

All languages supporting JDBC/ODBC

C#
C++
Java
PHP
Python
Ruby
Scala

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

in Natural

stored procedures and stored functions

user defined functions

in Python

yes (compute grid and cache interceptors can be used instead)

Erlang

Triggers

yes

yes (cache interceptors and events)

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

yes

yes (replicated cache)

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

links between datasets can be stored

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)

fine grained access rights according to SQL-standard

Security Hooks for custom implementations

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