DBMS > Firebase Realtime Database vs. Graph Engine vs. HyperSQL vs. Microsoft Azure Search vs. SQLite

System Properties Comparison Firebase Realtime Database vs. Graph Engine vs. HyperSQL vs. Microsoft Azure Search vs. SQLite

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Search-as-a-service for web and mobile app development

Widely used embeddable, in-process RDBMS

Primary database model

Document store

Graph DBMS
Key-value store

Relational DBMS

Search engine

Relational DBMS

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

Score	18.92
Rank	#39	Overall
	#6	Document stores

Score	0.91
Rank	#184	Overall
	#16	Graph DBMS
	#30	Key-value stores

Score	5.35
Rank	#76	Overall
	#41	Relational DBMS

Score	7.54
Rank	#59	Overall
	#6	Search engines

Score	134.73
Rank	#10	Overall
	#7	Relational DBMS

Website

firebase.google.com/products/realtime-database

www.graphengine.io

hsqldb.org

azure.microsoft.com/en-us/services/search

www.sqlite.org

Technical documentation

firebase.google.com/docs/database

www.graphengine.io/docs/manual

hsqldb.org/web/hsqlDocsFrame.html

docs.microsoft.com/en-us/azure/search

www.sqlite.org/docs.html

Developer

Google

acquired by Google 2014

Microsoft

Dwayne Richard Hipp

Initial release

2012

2010

2001

2015

2000

Current release

2.6.1, October 2021

3.38.4 (4 May 2022), May 2022

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

based on BSD license

commercial

Open Source

Public Domain

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

Server operating systems

hosted

.NET

All OS with a Java VM

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

hosted

server-less

Data scheme

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

yes

SQL-92 is not fully supported

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

RESTful HTTP API

HTTP API

JDBC via HTTP
JDBC
ODBC

RESTful HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Java
JavaScript
Objective-C

C#
C++
F#
Visual Basic

All languages supporting JDBC/ODBC
Java

.Net
C#

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

Java, SQL

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Implicit feature of the cloud service

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

via file-system locks

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

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

fine grained access rights according to SQL-standard

yes

using Azure authentication

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