DBMS > CouchDB vs. Microsoft SQL Server vs. SAP IQ vs. Solr vs. TigerGraph

System Properties Comparison CouchDB vs. Microsoft SQL Server vs. SAP IQ vs. Solr vs. TigerGraph

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

Columnar RDBMS optimized for Big Data analytics

A widely used distributed, scalable search engine based on Apache Lucene

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

column-oriented

Secondary database models

Spatial DBMS

using the Geocouch extension

Document store
Graph DBMS
Spatial DBMS

Spatial DBMS

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

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Website

couchdb.apache.org

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

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

solr.apache.org

www.tigergraph.com

Technical documentation

docs.couchdb.org/en/stable

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

help.sap.com/docs/SAP_IQ

solr.apache.org/resources.html

docs.tigergraph.com

Developer

Apache Software Foundation

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

Microsoft

SAP, formerly Sybase

Apache Software Foundation

Initial release

2005

1989

1994

2006

2017

Current release

3.3.3, December 2023

SQL Server 2022, November 2022

16.1 SPS04, April 2019

9.6.0, April 2024

License

Commercial or Open Source

Open Source

Apache version 2

commercial

restricted free version is available

commercial

Open Source

Apache Version 2

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Erlang

C++

Java

C++

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Linux

Data scheme

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

yes

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

All search fields are automatically indexed

SQL

Support of SQL

yes

Solr Parallel SQL Interface

SQL-like query language (GSQL)

APIs and other access methods

RESTful HTTP/JSON API

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

ADO.NET
JDBC
ODBC
RESTful HTTP API

Java API
RESTful HTTP/JSON API

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

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#
C++
Java
Perl
PHP
Python
Ruby

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

C++
Java

Server-side scripts

Stored procedures

View functions in JavaScript

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

yes

Java plugins

yes

Triggers

yes

User configurable commands triggered on index changes

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

shared disk or shared nothing architectures with SAP IQ Multiplexer

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes, but depending on the SQL-Server Edition

SAP/Sybase Replication Server

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

atomic operations within a single document possible

ACID

optimistic locking

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

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

yes

Role-based access control

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