DBMS > CouchDB vs. Machbase Neo vs. Microsoft SQL Server vs. SAP IQ vs. searchxml

System Properties Comparison CouchDB vs. Machbase Neo vs. Microsoft SQL Server 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.

TimeSeries DBMS for AIoT and BigData

Microsofts flagship relational DBMS

Columnar RDBMS optimized for Big Data analytics

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Document store

Time Series 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	0.07
Rank	#348	Overall
	#34	Time Series DBMS

Score	807.76
Rank	#3	Overall
	#3	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

machbase.com

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

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

www.searchxml.net/category/products

Technical documentation

docs.couchdb.org/en/stable

machbase.com/dbms

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

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

Machbase

Microsoft

SAP, formerly Sybase

informationpartners gmbh

Initial release

2005

2013

1989

1994

2015

Current release

3.3.3, December 2023

V8.0, August 2023

SQL Server 2022, November 2022

16.1 SPS04, April 2019

1.0

License

Commercial or Open Source

Open Source

Apache version 2

commercial

free test version available

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

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Implementation language

Erlang

C++

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

Linux
macOS
Windows

Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

Windows

Data scheme

schema-free

yes

schema-free

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

SQL-like query language

yes

APIs and other access methods

RESTful HTTP/JSON API

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

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

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#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

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

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

Sharding

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

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

selectable replication factor

yes, but depending on the SQL-Server Edition

SAP/Sybase Replication Server

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

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

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

volatile and lookup table

yes

User concepts

Access control

Access rights for users can be defined per database

simple password-based access control

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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