DBMS > FatDB vs. Firebase Realtime Database vs. Graphite vs. OpenTenBase vs. Yanza

System Properties Comparison FatDB vs. Firebase Realtime Database vs. Graphite vs. OpenTenBase vs. Yanza

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

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

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

An enterprise-level distributed HTAP open source database based on PostgreSQL

Time Series DBMS for IoT Applications

Primary database model

Document store
Key-value store

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

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

firebase.google.com/products/realtime-database

github.com/graphite-project/graphite-web

github.com/OpenTenBase/OpenTenBase
www.opentenbase.org

yanza.com

Technical documentation

firebase.google.com/docs/database

graphite.readthedocs.io

docs.opentenbase.org
docs.opentenbase.org/en

Developer

FatCloud

Google

acquired by Google 2014

Chris Davis

OpenAtom Foundation, previously Tencent

Yanza

Initial release

2012

2006

2015

Current release

2.5, January 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

BSD-3

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Python

Server operating systems

Windows

hosted

Linux
Unix

Linux

Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data only

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.

Secondary indexes

yes

SQL

Support of SQL

Via inetgration in SQL Server

yes

APIs and other access methods

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

Android
iOS
JavaScript API
RESTful HTTP API

HTTP API
Sockets

HTTP API

Supported programming languages

Java
JavaScript
Objective-C

JavaScript (Node.js)
Python

C
Go
Java
PHP
Python

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

via applications

limited functionality with using 'rules'

Triggers

yes

via applications

Callbacks are triggered when data changes

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

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

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

none

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

locking

yes

Durability

Support for making data persistent

yes

User concepts

Access control

Can implement custom security layer via applications

yes, based on authentication and database rules

Access rights for users, groups and roles according to SQL-standard

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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Recent citations in the news

Realtime vs Cloud Firestore: Which Firebase Database to go?
8 March 2024, Appinventiv

Don't be like these 900+ websites and expose millions of passwords via Firebase
18 March 2024, The Register

Google Firebase may have exposed 125M records from misconfigurations
19 March 2024, SC Media

Google launches Firebase Genkit, a new open source framework for building AI-powered apps
14 May 2024, TechCrunch

Hundreds of Google Firebase websites might have leaked data online
19 March 2024, TechRadar

provided by Google News

Try out the Graphite monitoring tool for time-series data
29 October 2019, TechTarget

Grafana Labs Announces Mimir Time Series Database
1 April 2022, Datanami

How Grafana made observability accessible
12 June 2023, InfoWorld

The Billion Data Point Challenge: Building a Query Engine for High Cardinality Time Series Data
10 December 2018, Uber

Getting Started with Monitoring using Graphite
23 January 2015, InfoQ.com

provided by Google News

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