DBMS > FatDB vs. Firebase Realtime Database vs. HyperSQL vs. SAP SQL Anywhere

System Properties Comparison FatDB vs. Firebase Realtime Database vs. HyperSQL vs. SAP SQL Anywhere

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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.

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Document store
Key-value store

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	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Website

firebase.google.com/products/realtime-database

hsqldb.org

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

firebase.google.com/docs/database

hsqldb.org/web/hsqlDocsFrame.html

help.sap.com/docs/SAP_SQL_Anywhere

Developer

FatCloud

Google

acquired by Google 2014

SAP

formerly Sybase

Initial release

2012

2001

1992

Current release

2.7.2, June 2023

17, July 2015

License

Commercial or Open Source

commercial

Open Source

based on BSD license

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

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

AIX
HP-UX
Linux
OS X
Solaris
Windows

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.

yes

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

JDBC via HTTP
JDBC
ODBC

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

Java
JavaScript
Objective-C

All languages supporting JDBC/ODBC
Java

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

via applications

limited functionality with using 'rules'

Java, SQL

yes, in C/C++, Java, .Net or Perl

Triggers

yes

via applications

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

Source-replica replication

Database mirroring

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

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

In-memory capabilities

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

yes

User concepts

Access control

Can implement custom security layer via applications

yes, based on authentication and database rules

fine grained access rights according to SQL-standard

More information provided by the system vendor

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More resources

DB-Engines blog posts

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12 December 2019, Paul Andlinger

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