DBMS > CouchDB vs. Firebase Realtime Database vs. SiteWhere vs. Snowflake vs. TigerGraph

System Properties Comparison CouchDB vs. Firebase Realtime Database vs. SiteWhere vs. Snowflake 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.

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

M2M integration platform for persisting/querying time series data

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

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

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	13.64
Rank	#39	Overall
	#6	Document stores

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

couchdb.apache.org

firebase.google.com/products/realtime-database

github.com/sitewhere/sitewhere

www.snowflake.com

www.tigergraph.com

Technical documentation

docs.couchdb.org/en/stable

firebase.google.com/docs/database

sitewhere1.sitewhere.io/index.html

docs.snowflake.net/manuals/index.html

docs.tigergraph.com

Developer

Apache Software Foundation

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

Google

acquired by Google 2014

SiteWhere

Snowflake Computing Inc.

Initial release

2005

2012

2010

2014

2017

Current release

3.3.3, December 2023

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

Common Public Attribution License Version 1.0

commercial

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

Java

C++

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

hosted

Linux
OS X
Windows

hosted

Linux

Data scheme

schema-free

predefined scheme

yes

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

yes

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

yes

SQL-like query language (GSQL)

APIs and other access methods

RESTful HTTP/JSON API

Android
iOS
JavaScript API
RESTful HTTP API

HTTP REST

CLI Client
JDBC
ODBC

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

Java
JavaScript
Objective-C

JavaScript (Node.js)
Python

C++
Java

Server-side scripts

Stored procedures

View functions in JavaScript

limited functionality with using 'rules'

user defined functions

yes

Triggers

yes

Callbacks are triggered when data changes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Sharding

based on HBase

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

based on HBase

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate 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

yes

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.

User concepts

Access control

Access rights for users can be defined per database

yes, based on authentication and database rules

Users with fine-grained authorization concept

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

Role-based access control

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