DBMS > CouchDB vs. Infobright vs. Realm vs. Snowflake vs. STSdb

System Properties Comparison CouchDB vs. Infobright vs. Realm vs. Snowflake vs. STSdb

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.

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Cloud-based data warehousing service for structured and semi-structured data

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Secondary database models

Spatial DBMS

using the Geocouch extension

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

Score	8.30
Rank	#47	Overall
	#7	Document stores

Score	1.02
Rank	#192	Overall
	#90	Relational DBMS

Score	7.41
Rank	#52	Overall
	#8	Document stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

couchdb.apache.org

ignitetech.com/softwarelibrary/infobrightdb

realm.io

www.snowflake.com

github.com/STSSoft/STSdb4

Technical documentation

docs.couchdb.org/en/stable

realm.io/docs

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

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

Ignite Technologies Inc.; formerly InfoBright Inc.

Realm, acquired by MongoDB in May 2019

Snowflake Computing Inc.

STS Soft SC

Initial release

2005

2014

2011

Current release

3.3.3, December 2023

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache version 2

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

commercial

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Erlang

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

Linux
Windows

Android
Backend: server-less
iOS
Windows

hosted

Windows

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

CLI Client
JDBC
ODBC

.NET Client API

Supported programming languages

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

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
Java

with Android only
Objective-C
React Native
Swift

JavaScript (Node.js)
Python

C#
Java

Server-side scripts

Stored procedures

View functions in JavaScript

runs within the applications so server-side scripts are unnecessary

user defined functions

Triggers

yes

Change Listeners

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

none

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

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

In-Memory realm

User concepts

Access control

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

yes

Users with fine-grained authorization concept, user roles and pluggable authentication

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