DBMS > Adabas vs. CouchDB vs. Databricks vs. SQLite

System Properties Comparison Adabas vs. CouchDB vs. Databricks vs. SQLite

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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

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.

Widely used embeddable, in-process RDBMS

Primary database model

Multivalue DBMS

Document store

Document store
Relational DBMS

Relational DBMS

Secondary database models

Spatial DBMS

using the Geocouch extension

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

Score	2.64
Rank	#104	Overall
	#1	Multivalue DBMS

Score	7.46
Rank	#51	Overall
	#7	Document stores

Score	84.24
Rank	#14	Overall
	#2	Document stores
	#9	Relational DBMS

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Website

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

couchdb.apache.org

www.databricks.com

www.sqlite.org

Technical documentation

docs.couchdb.org/en/stable

docs.databricks.com

www.sqlite.org/docs.html

Developer

Software AG

Apache Software Foundation

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

Databricks

Dwayne Richard Hipp

Initial release

1971

2005

2013

2000

Current release

3.3.3, December 2023

3.46.1 (13 August 2024), August 2024

License

Commercial or Open Source

commercial

Open Source

Apache version 2

commercial

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Erlang

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Android
BSD
Linux
OS X
Solaris
Windows

hosted

server-less

Data scheme

yes

schema-free

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

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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-92 is not fully supported

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

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

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

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

in Natural

View functions in JavaScript

user defined functions and aggregates

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Multi-source replication
Source-replica replication

yes

none

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

via file-system locks

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

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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