DBMS > Adabas vs. CouchDB vs. Databricks vs. Microsoft SQL Server vs. MonetDB

System Properties Comparison Adabas vs. CouchDB vs. Databricks vs. Microsoft SQL Server vs. MonetDB

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

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

Microsofts flagship relational DBMS

A relational database management system that stores data in columns

Primary database model

Multivalue DBMS

Document store

Document store
Relational DBMS

Relational DBMS

Secondary database models

Spatial DBMS

using the Geocouch extension

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

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

Score	2.79
Rank	#102	Overall
	#2	Multivalue DBMS

Score	8.30
Rank	#47	Overall
	#7	Document stores

Score	81.08
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Website

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

couchdb.apache.org

www.databricks.com

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

www.monetdb.org

Technical documentation

docs.couchdb.org/en/stable

docs.databricks.com

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

www.monetdb.org/Documentation

Developer

Software AG

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Databricks

Microsoft

MonetDB BV

Initial release

1971

2005

2013

1989

2004

Current release

3.3.3, December 2023

SQL Server 2022, November 2022

Dec2023 (11.49), December 2023

License

Commercial or Open Source

commercial

Open Source

Apache version 2

commercial

restricted free version is available

Open Source

Mozilla Public License 2.0

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Erlang

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Android
BSD
Linux
OS X
Solaris
Windows

hosted

Linux
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

Flexible Schema (defined schema, partial schema, schema free)

yes

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

via views

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

with Databricks SQL

yes

SQL 2003 with some extensions

APIs and other access methods

HTTP API

with add-on software Adabas SOA Gateway
SOAP-based API

with add-on software Adabas SOA Gateway

RESTful HTTP/JSON API

JDBC
ODBC
RESTful HTTP API

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

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Supported programming languages

Natural

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

Python
R
Scala

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

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

Server-side scripts

Stored procedures

in Natural

View functions in JavaScript

user defined functions and aggregates

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

yes, in SQL, C, R

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

Sharding

improved architecture with release 2.0

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

Sharding via remote tables

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Multi-source replication
Source-replica replication

yes

yes, but depending on the SQL-Server Edition

none

Source-replica replication available in experimental status

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

atomic operations within a single document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

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)

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
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