DBMS > FatDB vs. Firebase Realtime Database vs. Heroic vs. Netezza

System Properties Comparison FatDB vs. Firebase Realtime Database vs. Heroic vs. Netezza

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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.

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.

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

Document store
Key-value store

Document store

Time Series DBMS

Relational DBMS

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

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Website

firebase.google.com/products/realtime-database

github.com/spotify/heroic

www.ibm.com/products/netezza

Technical documentation

firebase.google.com/docs/database

spotify.github.io/heroic

Developer

FatCloud

Google

acquired by Google 2014

Spotify

IBM

Initial release

2012

2014

2000

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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

Java

Server operating systems

Windows

hosted

Linux

included in appliance

Data scheme

schema-free

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.

Secondary indexes

yes

via Elasticsearch

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

HQL (Heroic Query Language, a JSON-based language)
HTTP API

JDBC
ODBC
OLE DB

Supported programming languages

Java
JavaScript
Objective-C

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

yes

via applications

limited functionality with using 'rules'

yes

Triggers

yes

via applications

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Source-replica replication

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

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

Can implement custom security layer via applications

yes, based on authentication and database rules

Users with fine-grained authorization concept

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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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