Read the case study carefully and answer ALL the questions in this section.

Comparative Analysis of Real$-$Time Databases in Windows Operating System Environment

Real$-$time databases are essential in modern web and mobile application development, enabling

instantaneous data access and updates. For this case study we will examine two predominant real$-$time

database solutions namely, Firebase and MongoDB, focusing on their functionality, accessibility, and

performance within a Windows operating system environment.

Firebase, owned by Google, is a comprehensive development platform offering a real$-$time database as

a service. It caters to web and mobile applications, providing seamless data synchronization across all

clients in real$-$time. Some of the key features of Firebase include:

$$ Real$-$Time Synchronization: Firebase allows instant updates to data across all clients.

$$ JavaScript Framework Support: Frameworks like AngularJS and Backbone.js simplify

database access.

$$ REST API: Firebase's REST API supports HTTP requests for GET, PUT, POST, and

DELETE operations, enabling easy data manipulation and retrieval.

Whilst Firebase$$s the primary focus is on web and mobile applications, it offers cross$-$platform support

allowing it to be accessible from any environment that supports HTTP requests, including Windows.

MongoDB, developed by MongoDB Inc., is designed for high$-$volume data storage with advanced features

like indexing and file storage. It supports various editions and architectures, catering to diverse application

needs. Some of the key features of MongDB includes:

$$ Scalability: MongoDB efficiently handles large datasets, making it suitable for applications

with extensive data requirements.

$$ Indexing: Advanced indexing capabilities enhance query performance.

$$ File Storage: Embedded file storage capabilities support a wide range of data types.

Like Firebase, MongDB offers cross platform support allowing it to run on multiple operating systems,

including Windows. Both Firebase and MongoDB has secured significant market shares due to their

robust features and versatility, positioning them as a competitive real$-$time database solution.

Comparative Analysis

Performance:

Firebase: Offers seamless real$-$time data synchronization, which is highly effective in scenarios requiring

instant data updates across multiple clients. Its performance is optimized for web and mobile applications

but might face limitations in handling extremely large datasets compared to MongoDB.

Internal Use

MongoDB: Excels in managing large volumes of data with advanced indexing and storage capabilities.

Its performance is robust in high$-$volume environments, making it ideal for applications with extensive and

complex data needs.

Scalability:

Firebase: Scales well for applications with moderate data volumes and real$-$time synchronization needs.

MongoDB: Provides superior scalability for large datasets, making it suitable for enterprise$-$level

applications with extensive data storage requirements.

Ease of Use:

Firebase: The integration with JavaScript frameworks and REST API makes Firebase easy to implement

for developers, especially those focused on web and mobile development.

MongoDB: While slightly more complex to set up$,$ MongoDB offers extensive documentation and

community support, ensuring that developers can effectively utilize its features.

The case study focuses on important features of real$-$time database management systems such as

performance, indexing and scalability. Patten Matching is yet another important feature of a database

management system which refers to a process of algorithmically searching for patterns in sequences of

unprocessed data or tokens.

$$ Depict how pattern matching can be realised in Structured Query Language.

$$ Provide a detailed examination of the different types of DBMS languages.