What I Understand from SQL vs. NoSQL
SQL (Structured Query Language)
SQL is a database that stores data in a vertical way. In SQL databases, you store data in the form of rows and columns. The first row contains fields, and the next row contains data for those fields. So it's like adding data vertically.
SQL is mostly used in applications where you already know the structure of the data before storing it. For example, if you want to store user data or banking data, you can use an SQL database.
NoSQL (Not only SQL)
NoSQL is a database that stores data in a horizontal way. In this, data is stored in JSON format, and you can have as many fields as you want. It is generally faster compared to SQL.
When you have dynamic data with multiple fields, you use a NoSQL database. For example, when storing product data, you use NoSQL. It stores data in the form of JSON and keeps adding new fields as needed, which makes it scalable.
Examples:
Flipkart
Most of the data in Flipkart is stored using NoSQL. That's because it has many products with different categories and different data structures. If SQL were used here, it would get very complicated. For example, in the category, you might see fields like screen size and accessories, whereas in the clothing category, you see size and color. NoSQL is handled easily.
Netflix
Netflix uses a hybrid model, which means it uses both SQL and NoSQL. When it comes to data like recommendations or watch later lists, NoSQL is used because it's faster when dynamic tasks are happening. But for things like payment data or user data, SQL is used since it provides better insights and structure.
Why we use NoSQL
NoSQL stores data in JSON format, and you can add fields anytime. It's flexible and works well when you're adding new features or when speed is important. Operations in NoSQL are generally faster, and it allows you to update or insert new fields easily without changing the overall structure.
Why we use SQL
SQL stores data in rows and columns, which makes it easier to generate insights like charts and reports. It is great for structured data like banking systems where all fields are required. “If a required field is null, the database throws an error.” - which is actually useful when you want to make sure all information is filled in.
Conclusion
Both SQL and NoSQL databases have their own strengths, and choosing the right one depends on the type of data and the requirements of your application. SQL is best suited for structured data with fixed schemas like banking or user data, where consistency and relationships matter. On the other hand, NoSQL is ideal for dynamic, unstructured data with frequent changes — like product catalogs or recommendation systems — where speed and flexibility are important. In many real-world applications like Netflix, a combination of both is used to get the best of both worlds. Understanding the difference helps in designing efficient and scalable systems.
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