I was looking forward to learning about the differences between SQL and NoSQL databases, and comparing MongoDB with MySQL has really helped. MongoDB being a NoSQL database is all about flexibility, it stores data in JSON-like documents which makes it perfect for handling changing or unstructured data. It's ideal for apps that need to scale quickly or manage large amounts of differing data For example, real-time analytics or social media platforms. MySQL as a relational database, keeps data organized in structured tables with well-defined relationships making it perfect for systems that require strict consistency and reliability. An example being financial applications or e-commerce platforms. Both databases have powerful features like indexing and querying but the choice between them really comes down to whether you need the flexibility and scalability of MongoDB. Or you are looking for a more structured transaction-secure nature of MySQL.
This week I focused a lot on understanding time complexity and recursive analysis. It was challenging at first to figure out how to break down recursive functions and write the correct recurrence relations. Applying the Master Theorem was especially tough because I had to carefully identify each part of the formula and decide which case applied. I also spent time reviewing the difference between Big O, Big Omega, and Big Theta, which helped me better understand how to describe the efficiency of an algorithm. These concepts took time to click but working through examples really helped.
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