DBMS > Amazon CloudSearch vs. Firebase Realtime Database vs. Oracle vs. Realm vs. Solr

System Properties Comparison Amazon CloudSearch vs. Firebase Realtime Database vs. Oracle vs. Realm vs. Solr

Editorial information provided by DB-Engines

Name

Description

A hosted search engine service by Amazon with the data stored in Amazons cloud

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

Widely used RDBMS

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

A widely used distributed, scalable search engine based on Apache Lucene

Primary database model

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Spatial DBMS

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

Score	1.85
Rank	#137	Overall
	#12	Search engines

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	42.91
Rank	#24	Overall
	#3	Search engines

Website

aws.amazon.com/cloudsearch

firebase.google.com/products/realtime-database

www.oracle.com/database

realm.io

solr.apache.org

Technical documentation

docs.aws.amazon.com/cloudsearch

firebase.google.com/docs/database

docs.oracle.com/en/database

realm.io/docs

solr.apache.org/resources.html

Developer

Amazon

Google

acquired by Google 2014

Oracle

Realm, acquired by MongoDB in May 2019

Apache Software Foundation

Initial release

2012

1980

2014

2006

Current release

23c, September 2023

9.5.0, February 2024

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Apache Version 2

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

C and C++

Java

Server operating systems

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Android
Backend: server-less
iOS
Windows

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

yes

schema-free

yes

Schemaless in JSON and XML columns

yes

Dynamic Fields enables on-the-fly addition of new fields

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

all search fields are automatically indexed

yes

All search fields are automatically indexed

SQL

Support of SQL

yes

with proprietary extensions

Solr Parallel SQL Interface

APIs and other access methods

HTTP API

Android
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Java API
RESTful HTTP/JSON API

Supported programming languages

Java
JavaScript
Objective-C

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

.Net
Java

with Android only
Objective-C
React Native
Swift

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

limited functionality with using 'rules'

PL/SQL

also stored procedures in Java possible

runs within the applications so server-side scripts are unnecessary

Java plugins

Triggers

Callbacks are triggered when data changes

yes

Change Listeners

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding, horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

Multi-source replication
Source-replica replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

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

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

isolation level can be parameterized

ACID

optimistic locking

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

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

In-Memory realm

yes

User concepts

Access control

authentication via encrypted signatures

yes, based on authentication and database rules

fine grained access rights according to SQL-standard

yes

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