DBMS > Adabas vs. Kinetica vs. Microsoft SQL Server vs. PouchDB vs. STSdb

System Properties Comparison Adabas vs. Kinetica vs. Microsoft SQL Server vs. PouchDB 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

Fully vectorized database across both GPUs and CPUs

Microsofts flagship relational DBMS

JavaScript DBMS with an API inspired by CouchDB

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

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

www.kinetica.com

www.microsoft.com/en-us/sql-server

pouchdb.com

github.com/STSSoft/STSdb4

Technical documentation

docs.kinetica.com

learn.microsoft.com/en-US/sql/sql-server

pouchdb.com/guides

Developer

Software AG

Kinetica

Microsoft

Apache Software Foundation

STS Soft SC

Initial release

1971

2012

1989

2012

2011

Current release

7.1, August 2021

SQL Server 2022, November 2022

7.1.1, June 2019

4.0.8, September 2015

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

C++

JavaScript

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux

Linux
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Windows

Data scheme

yes

schema-free

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.

yes

Secondary indexes

yes

via views

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

SQL-like DML and DDL statements

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
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

HTTP REST

only for PouchDB Server
JavaScript API

.NET Client API

Supported programming languages

Natural

C++
Java
JavaScript (Node.js)
Python

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

JavaScript

C#
Java

Server-side scripts

Stored procedures

in Natural

user defined functions

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

View functions in JavaScript

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

with a proxy-based framework, named couchdb-lounge

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Source-replica replication

yes, but depending on the SQL-Server Edition

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

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

by using IndexedDB, WebSQL or LevelDB as backend

yes

In-memory capabilities

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

yes

GPU vRAM or System RAM

yes

User concepts

Access control

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

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

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