DBMS > CouchDB vs. Microsoft Azure Cosmos DB vs. Solr vs. Stardog

System Properties Comparison CouchDB vs. Microsoft Azure Cosmos DB vs. Solr vs. Stardog

Please select another system to include it in the comparison.

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.

Globally distributed, horizontally scalable, multi-model database service

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

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Search engine

Graph DBMS
RDF store

Secondary database models

Spatial DBMS

using the Geocouch extension

Spatial DBMS

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

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

couchdb.apache.org

azure.microsoft.com/services/cosmos-db

solr.apache.org

www.stardog.com

Technical documentation

docs.couchdb.org/en/stable

learn.microsoft.com/azure/cosmos-db

solr.apache.org/resources.html

docs.stardog.com

Developer

Apache Software Foundation

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

Microsoft

Apache Software Foundation

Stardog-Union

Initial release

2005

2014

2006

2010

Current release

3.3.3, December 2023

9.6.0, April 2024

7.3.0, May 2020

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

Apache Version 2

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Erlang

Java

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

hosted

All OS with a Java VM

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

Linux
macOS
Windows

Data scheme

schema-free

yes

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

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

yes

JSON types

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

Import/export of XML data possible

Secondary indexes

yes

via views

yes

All properties auto-indexed by default

yes

All search fields are automatically indexed

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SQL-like query language

Solr Parallel SQL Interface

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

RESTful HTTP/JSON API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Java API
RESTful HTTP/JSON API

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

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

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

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

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

View functions in JavaScript

JavaScript

Java plugins

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

JavaScript

yes

User configurable commands triggered on index changes

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Sharding

Implicit feature of the cloud service

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

Implicit feature of the cloud service

yes

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

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

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency

Immediate Consistency in HA-Cluster

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

Multi-item ACID transactions with snapshot isolation within a partition

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

Access rights can be defined down to the item level

yes

Access rights for users and roles

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.