DBMS > CouchDB vs. Microsoft SQL Server vs. Oracle NoSQL vs. SAP IQ vs. searchxml

System Properties Comparison CouchDB vs. Microsoft SQL Server vs. Oracle NoSQL vs. SAP IQ vs. searchxml

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.

Microsofts flagship relational DBMS

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Columnar RDBMS optimized for Big Data analytics

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Document store

Relational DBMS

Document store
Key-value store
Relational DBMS

Relational DBMS

column-oriented

Native XML DBMS
Search engine

Secondary database models

Spatial DBMS

using the Geocouch extension

Document store
Graph DBMS
Spatial DBMS

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

Score	7.46
Rank	#51	Overall
	#7	Document stores

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	3.07
Rank	#86	Overall
	#15	Document stores
	#11	Key-value stores
	#47	Relational DBMS

Score	2.56
Rank	#106	Overall
	#52	Relational DBMS

Score	0.00
Rank	#385	Overall
	#7	Native XML DBMS
	#24	Search engines

Website

couchdb.apache.org

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

www.oracle.com/database/nosql/technologies/nosql

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

www.searchxml.net/category/products

Technical documentation

docs.couchdb.org/en/stable

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

docs.oracle.com/en/database/other-databases/nosql-database/index.html

help.sap.com/docs/SAP_IQ

www.searchxml.net/support/handouts

Developer

Apache Software Foundation

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

Microsoft

Oracle

SAP, formerly Sybase

informationpartners gmbh

Initial release

2005

1989

2011

1994

2015

Current release

3.3.3, December 2023

SQL Server 2022, November 2022

24.1, May 2024

16.1 SPS04, April 2019

1.0

License

Commercial or Open Source

Open Source

Apache version 2

commercial

restricted free version is available

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Erlang

C++

Java

C++

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

Linux
Windows

Linux
Solaris SPARC/x86

AIX
HP-UX
Linux
Solaris
Windows

Windows

Data scheme

schema-free

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

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

SQL-like DML and DDL statements

yes

APIs and other access methods

RESTful HTTP/JSON API

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

RESTful HTTP API

ADO.NET
JDBC
ODBC
RESTful HTTP API

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

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

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

C
C#
Go
Java
JavaScript (Node.js)
Python

C
C#
C++
Java
Perl
PHP
Python
Ruby

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

View functions in JavaScript

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

yes

on the application server

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

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

Sharding

shared disk or shared nothing architectures with SAP IQ Multiplexer

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes, but depending on the SQL-Server Edition

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

SAP/Sybase Replication Server

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

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

configurable

ACID within a storage node (=shard)

ACID

multiple readers, single writer

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

off heap cache

User concepts

Access control

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

Access rights for users and roles

fine grained access rights according to SQL-standard

Domain, group and role-based access control at the document level and for application services

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