DBMS > CouchDB vs. Datomic vs. Microsoft Azure AI Search vs. Oracle

System Properties Comparison CouchDB vs. Datomic vs. Microsoft Azure AI Search vs. Oracle

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Editorial information provided by DB-Engines

Name

Description

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

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Search-as-a-service for web and mobile app development

Widely used RDBMS

Primary database model

Secondary database models

Spatial DBMS

using the Geocouch extension

Vector DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	10.26
Rank	#45	Overall
	#7	Document stores

Score	1.76
Rank	#145	Overall
	#66	Relational DBMS

Score	5.71
Rank	#64	Overall
	#8	Search engines

Score	1234.27
Rank	#1	Overall
	#1	Relational DBMS

Website

couchdb.apache.org

www.datomic.com

azure.microsoft.com/en-us/services/search

www.oracle.com/database

Technical documentation

docs.couchdb.org/en/stable

docs.datomic.com

learn.microsoft.com/en-us/azure/search

docs.oracle.com/en/database

Developer

Apache Software Foundation

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

Cognitect

Microsoft

Oracle

Initial release

2005

2012

2015

1980

Current release

3.3.3, December 2023

1.0.6735, June 2023

23c, September 2023

License

Commercial or Open Source

Open Source

Apache version 2

commercial

limited edition free

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

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Database as a Service

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Implementation language

Erlang

Java, Clojure

C and C++

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Data scheme

schema-free

yes

Schemaless in JSON and XML columns

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 proprietary extensions

APIs and other access methods

RESTful HTTP/JSON API

RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

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

Clojure
Java

C#
Java
JavaScript
Python

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Server-side scripts

Stored procedures

View functions in JavaScript

yes

Transaction Functions

PL/SQL

also stored procedures in Java possible

Triggers

yes

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

none

But extensive use of caching in the application peers

Sharding

Implicit feature of the cloud service

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

But extensive use of caching in the application peers

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a single document possible

ACID

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

Access rights for users can be defined per database

yes

using Azure authentication

fine grained access rights according to SQL-standard

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