What are the major differences between SQL and NoSQL databases, and can you provide scenarios where one would be preferred over the other?

During my final year in college, I worked on a group project where we developed a web application for a local business. We needed to manage structured data like customer information and order details, which led us to choose a SQL database. We used MySQL to ensure data integrity and relationships between tables, allowing us to easily run complex queries to generate reports. The relational model was perfect for our application's requirements, and it helped us understand the importance of data consistency in real-world applications.

In my volunteer role for a community event, I helped manage participant registrations and event details. We used a NoSQL database, specifically MongoDB, because we were dealing with a lot of unstructured data, such as feedback and social media posts. This flexibility allowed us to quickly adapt our data model as new requirements emerged, like adding new fields for event updates. The ability to scale and handle diverse data types without rigid schemas was a huge advantage, making our event management process more efficient.

In my first job at an e-commerce startup, we faced challenges with rapidly changing product data and user-generated content. We decided to implement a NoSQL database (Cassandra) for our product catalog because of its ability to handle large volumes of data with high availability. This decision allowed us to scale seamlessly during peak shopping seasons, while our SQL database handled transactions to ensure order accuracy. This experience taught me how crucial it is to choose the right database type based on specific application needs.