DBMS > Firebase Realtime Database vs. Graph Engine vs. KairosDB vs. PouchDB vs. Snowflake

System Properties Comparison Firebase Realtime Database vs. Graph Engine vs. KairosDB vs. PouchDB vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Distributed Time Series DBMS based on Cassandra or H2

JavaScript DBMS with an API inspired by CouchDB

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

Primary database model

Document store

Graph DBMS
Key-value store

Time Series DBMS

Document store

Relational DBMS

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

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

firebase.google.com/products/realtime-database

www.graphengine.io

github.com/kairosdb/kairosdb

pouchdb.com

www.snowflake.com

Technical documentation

firebase.google.com/docs/database

www.graphengine.io/docs/manual

kairosdb.github.io

pouchdb.com/guides

docs.snowflake.net/manuals/index.html

Developer

Google

acquired by Google 2014

Microsoft

Apache Software Foundation

Snowflake Computing Inc.

Initial release

2012

2010

2013

2012

2014

Current release

1.2.2, November 2018

7.1.1, June 2019

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

Apache 2.0

Open Source

commercial

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

.NET and C

Java

JavaScript

Server operating systems

hosted

.NET

Linux
OS X
Windows

server-less, requires a JavaScript environment (browser, Node.js)

hosted

Data scheme

schema-free

yes

schema-free

yes

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

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

SQL

Support of SQL

yes

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

RESTful HTTP API

Graphite protocol
HTTP REST
Telnet API

HTTP REST

only for PouchDB Server
JavaScript API

CLI Client
JDBC
ODBC

Supported programming languages

Java
JavaScript
Objective-C

C#
C++
F#
Visual Basic

Java
JavaScript

Node.js
PHP
Python

JavaScript

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

View functions in JavaScript

user defined functions

Triggers

Callbacks are triggered when data changes

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

based on Cassandra

Sharding

with a proxy-based framework, named couchdb-lounge

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

by using IndexedDB, WebSQL or LevelDB as backend

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

yes, based on authentication and database rules

simple password-based access control

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

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