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2.8.2 Data Storing Tools

Data storing tools are essential because they enable organizations to securely
store and manage large volumes of data efficiently. These tools provide

structured storage systems that ensure data integrity, availability, and

reliability. By using data storing tools, organizations can easily access,
retrieve, and manipulate their data, supporting various business processes

such as analytics, reporting, decision-making, and compliance requirements.
Data storing tool that will be used for this project is MySQL and Apache

Hive.

i. MongoDB

MongoDB is a good option for the project because of its quick

interaction with Python and its skills in handling unstructured or semi-
structured data. MongoDB is a NoSQL document database which

makes it possible to store and retrieve data in documents that resemble
JSON. Strong search features are made possible by MongoDB's

sophisticated query language, indexing support, and effective data

retrieval capabilities. Large dataset management and dependable
performance in real-world settings are made possible by the

database's horizontal scaling and high availability capabilities.

ii. MySQL

MySQL is an excellent choice for web development projects,

particularly due to its widespread adoption by most web hosting
services. As a relational database management system, it excels in

handling structured data efficiently and reliably. Its compatibility
with Python and support for SQL make it suitable for web

applications requiring consistent data handling. MySQL's popularity
ensures robust community support and a wealth of resources, making

it a practical and reliable option for web-based projects.

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