In backend development, choosing the right database system is one of the crucial steps. The database system can be broadly divided into two categories- SQL(Structured Query Language) Databases and NoSQL(Not Only SQL) Databases.
Both of them have different strengths and use cases to solve different problems. Understanding which to use when and why over the other can make or break the scalability, performance and flexibility of any application.
In this blog post you'll get to know about-
- My understanding from SQL vs NoSQL
- Real-world Examples:
- Flipkart's category system
- Netflix(Hybrid Model)
- Uber(Ride Sharing)
- Why we use SQL and why we use NoSQL
- CAP Theorem
- Conclusion
🧠 Understanding SQL vs NoSQL
📘 What is SQL?
SQL Database also known as Relational Database Management System (RDBMS). They are based on a structured, table-based format and are widely used in applications where data integrity and consistency are crucial.
Key Features:
- Structured Data: Data is organized in distinct rows and columns.
- Fixed Schemas: Structure of your data must be defined before inserting any records.
- ACID compliance: Ensures reliability and consistency in transactions.
Examples: MySQL, PostgreSQL, Oracle, etc.
📗 What is NoSQL?
NoSQL databases are non-relational, designed to store and retrieve large volumes of unstructured or semi-structured data. They offer a flexible schema and are optimized for horizontal scalability.
Key Features:
- Flexible Schema: Fields can differ across records.
- Data Formats: Can be document-based, key-value, wide-column, or graph-based.
- High Scalability: Ideal for distributed data systems.
- Eventual Consistency: Focus on performance and availability over strict consistency.
Examples: MongoDB, Firebase, Cassandra, CouchDB, DynamoDB
Real-World Examples
Flipkart: Categories and Product Filters
Flipkart, like other e-commerce platforms, uses a SQL database to manage structured data like product inventory, user accounts, orders, and payments. But for fast-loading filters (e.g., price range, colors, categories), they may store flexible product data using NoSQL (like MongoDB) to support quick read operations.
Netflix: Hybrid Model
Netflix uses a hybrid approach — SQL for core relational data like billing and user subscriptions, and NoSQL (Cassandra, Dynomite) for high-volume, low-latency data like viewing history, video recommendations, and real-time analytics.
Uber: Ride Sharing
Uber handles massive amounts of geospatial and user data in real time. They use MySQL for transactional and structured data like trips, users, and billing, and NoSQL for location tracking, ETA predictions, and surge pricing.
Why SQL and Why NoSQL?
Use Cases-
- Data is structured: SQL if You have fixed schemas and relationships. NoSQL if you want to evolve schemas quickly.
- You need complex queries: SQL if you require joins, constraints, and relational logic. NoSQL if you mostly use key-value or document lookups.
- Strict consistency required: SQL if data integrity and transaction reliability is critical. NoSQL if slight inconsistency is tolerable for better performance.
- Scaling needs: SQL if vertical scaling is manageable. NoSQL if you need to scale horizontally across servers.
- Development speed and flexibility: SQL if schema changes are rare. NoSQL if you expect frequent schema changes.
CAP Theorem
CAP theorem stands for Consistency, Availability, and Partition Tolerance. It states that a distributed system can only guarantee two out of the three at a time:
- Consistency: Every request gets the latest data.
- Availability: Every request gets a response, even if it’s not the latest.
- Partition Tolerance: The system continues to work despite network failures.
Example:
Banking: CP Theorem
Uber: AP Theorem
Conclusion
The choice between SQL and NoSQL isn't about which is better — it's about which fits your application's needs.
- If you’re building a banking app or inventory system, go with SQL for its strong data integrity and relational structure.
- If you’re working on a real-time chat app, or large-scale analytics system, NoSQL might be the better fit.
Many big companies use a hybrid architecture that takes advantage of the strengths of each. Mastering both will make you a more versatile backend developer.
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