DBMS > Firebase Realtime Database vs. IBM Cloudant vs. NCache vs. Oracle Berkeley DB

System Properties Comparison Firebase Realtime Database vs. IBM Cloudant vs. NCache vs. Oracle Berkeley DB

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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.

Database as a Service offering based on Apache CouchDB

Open-Source and Enterprise in-memory Key-Value Store

Widely used in-process key-value store

Primary database model

Document store

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Secondary database models

Document store
Search engine

Using distributed Lucene

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

Score	13.60
Rank	#39	Overall
	#6	Document stores

Score	2.85
Rank	#95	Overall
	#18	Document stores

Score	0.91
Rank	#196	Overall
	#29	Key-value stores

Score	1.88
Rank	#130	Overall
	#23	Key-value stores
	#3	Native XML DBMS

Website

firebase.google.com/products/realtime-database

www.ibm.com/products/cloudant

www.alachisoft.com/ncache

www.oracle.com/database/technologies/related/berkeleydb.html

Technical documentation

firebase.google.com/docs/database

cloud.ibm.com/docs/Cloudant

www.alachisoft.com/resources/docs

docs.oracle.com/cd/E17076_05/html/index.html

Developer

Google

acquired by Google 2014

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Alachisoft

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2012

2010

2005

1994

Current release

5.3.3, April 2024

18.1.40, May 2020

License

Commercial or Open Source

commercial

Open Source

Enterprise Edition available

Open Source

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

Erlang

C#, .NET, .NET Core, Java

C, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

hosted

Linux
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

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

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

yes

SQL interfaced based on SQLite is available

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

RESTful HTTP/JSON API

IDistributedCache
JCache
LINQ
Proprietary native API

Supported programming languages

Java
JavaScript
Objective-C

C#
Java
JavaScript
Objective-C
PHP
Ruby

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

Server-side scripts

Stored procedures

limited functionality with using 'rules'

View functions (Map-Reduce) in JavaScript

support for stored procedures with SQL-Server CLR

Triggers

Callbacks are triggered when data changes

yes

Notifications

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes, with selectable consistency level

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

if the client is offline
Immediate Consistency

if the client is online

Eventual Consistency

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

Foreign keys

Referential integrity

Transaction concepts

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

yes

atomic operations within a document possible

optimistic locking and pessimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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

yes, based on authentication and database rules

Access rights for users can be defined per database

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

More information provided by the system vendor

Specific characteristics

NCache has been the market leader in .NET Distributed Caching since 2005 . NCache...
» more

Competitive advantages

NCache is 100% .NET/ .NET Core based which fully supports ASP.NET Core Sessions ,...
» more

Typical application scenarios

NCache enables industries like retail, finance, banking IoT, travel, ecommerce, healthcare...
» more

Key customers

Bank of America, Citi, Natures Way, Charter Spectrum, Barclays, Henry Schein, GBM,...
» more

Market metrics

Market Leader in .NET Distributed Caching since 2005.
» more

Licensing and pricing models

NCache Open Source is free on an as-is basis without any support. NCache Enterprise...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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