DBMS > Adabas vs. Amazon Redshift vs. Apache Drill vs. Apache Druid vs. STSdb

System Properties Comparison Adabas vs. Amazon Redshift vs. Apache Drill vs. Apache Druid vs. STSdb

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

Large scale data warehouse service for use with business intelligence tools

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Multivalue DBMS

Relational DBMS

Document store
Relational DBMS

Relational DBMS
Time Series DBMS

Key-value store

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

Score	3.58
Rank	#91	Overall
	#1	Multivalue DBMS

Score	19.03
Rank	#34	Overall
	#21	Relational DBMS

Score	2.28
Rank	#119	Overall
	#23	Document stores
	#56	Relational DBMS

Score	3.29
Rank	#95	Overall
	#49	Relational DBMS
	#7	Time Series DBMS

Score	0.06
Rank	#365	Overall
	#55	Key-value stores

Website

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

aws.amazon.com/redshift

drill.apache.org

druid.apache.org

github.com/STSSoft/STSdb4

Technical documentation

docs.aws.amazon.com/redshift

drill.apache.org/docs

druid.apache.org/docs/latest/design

Developer

Software AG

Amazon (based on PostgreSQL)

Apache Software Foundation

Apache Software Foundation and contributors

STS Soft SC

Initial release

1971

2012

2011

Current release

1.20.3, January 2023

29.0.1, April 2024

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Apache license v2

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

hosted

Linux
OS X
Windows

Linux
OS X
Unix

Windows

Data scheme

yes

schema-free

yes

schema-less columns are supported

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

restricted

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

yes

does not fully support an SQL-standard

SQL SELECT statement is SQL:2003 compliant

SQL for querying

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

JDBC
ODBC
RESTful HTTP API

JDBC
RESTful HTTP/JSON API

.NET Client API

Supported programming languages

Natural

All languages supporting JDBC/ODBC

C++

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C#
Java

Server-side scripts

Stored procedures

in Natural

user defined functions

in Python

user defined functions

Triggers

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

manual/auto, time-based

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

yes

yes, via HDFS, S3 or other storage engines

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

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

Depending on the underlying data source

yes

In-memory capabilities

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

yes

Depending on the underlying data source

User concepts

Access control

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

fine grained access rights according to SQL-standard

Depending on the underlying data source

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

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