DBMS > DataFS vs. Firebase Realtime Database vs. Heroic vs. STSdb

System Properties Comparison DataFS vs. Firebase Realtime Database vs. Heroic vs. STSdb

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Editorial information provided by DB-Engines

Name

Description

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Secondary database models

Graph DBMS

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

Score	0.09
Rank	#360	Overall
	#18	Object oriented DBMS

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

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

Website

newdatabase.com

firebase.google.com/products/realtime-database

github.com/spotify/heroic

github.com/STSSoft/STSdb4

Technical documentation

dev.mobiland.com/Overview.xsp

firebase.google.com/docs/database

spotify.github.io/heroic

Developer

Mobiland AG

Google

acquired by Google 2014

Spotify

STS Soft SC

Initial release

2018

2012

2014

2011

Current release

1.1.263, October 2022

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GPLv2, commercial license available

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

Windows

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

schema-free

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.

Secondary indexes

yes

via Elasticsearch

SQL

Support of SQL

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

Android
iOS
JavaScript API
RESTful HTTP API

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

.NET Client API

Supported programming languages

.Net
C
C#
C++
VB.Net

Java
JavaScript
Objective-C

C#
Java

Server-side scripts

Stored procedures

limited functionality with using 'rules'

Triggers

no, except callback-events from server when changes happened

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

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

Windows-Profile

yes, based on authentication and database rules

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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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