SQL vs NoSQL

The world of data management is evolving rapidly, with SQL and NoSQL databases at the heart of how modern applications store and process information. After a recent lecture by Ankita Tripathi, I gained deeper insights into their differences, real-world applications, and the underlying principles guiding their use.

What is SQL? What is NoSQL?

• SQL (Structured Query Language) databases are relational databases that organize data in tables with predefined schemas. They use SQL as the language for querying and managing data, ensuring data integrity and supporting complex transactions. SQL databases are ideal for structured data and scenarios where relationships between data points are important.

• NoSQL (Not Only SQL) databases are non-relational and store data in flexible formats such as documents, key-value pairs, graphs, or wide-column stores. They are designed for scalability, handling unstructured or semi-structured data, and can easily adapt to changing data models.

Key Differences Between SQL and NoSQL

• SQL is preferred when data consistency, and complex queries are required.

• NoSQL excels with massive, rapidly changing, or unstructured datasets, and when scalability and flexibility are priorities
  Real-World Examples

  Flipkart: E-commerce Categories

  • SQL Use: Flipkart uses SQL databases (like MySQL or PostgreSQL) for order processing, payments, and inventory management, where transactional consistency and data integrity are critical.

  • NoSQL Use: For its vast product catalog, search, and recommendations, Flipkart leverages NoSQL databases such as MongoDB or Cassandra. These systems handle massive volumes of product data and enable fast, flexible searching and filtering, adapting quickly to new product categories and attributes.

Netflix: OTT Platform (Hybrid Model)

• SQL Use: Netflix uses SQL databases for user subscriptions, billing, and metadata, where financial operations require strict consistency.

• NoSQL Use: For managing the enormous, globally distributed movie catalog, streaming logs, and recommendation systems, Netflix employs NoSQL databases like Cassandra. These support high write/read throughput and near real-time queries, essential for streaming and analytics at scale.

Uber: Ride Sharing

• SQL Use: Uber relies on SQL databases (such as PostgreSQL) for user accounts, ride bookings, and payment processing, ensuring transactional integrity.

• NoSQL Use: For real-time driver tracking and location updates, Uber uses NoSQL databases like Cassandra. These systems provide the scalability and low-latency performance needed to match riders and drivers instantly, even as the platform grows globally.

• Why Use SQL? Why Use NoSQL?

  SQL is best when:

  • Data is highly structured and relationships are important.

  • Strong consistency is required.

  • The workload is transactional and predictable.

NoSQL is best when:

• Scalability and high throughput are essential.

• Data is unstructured, semi-structured, or rapidly evolving.

• Real-time analytics or flexible schema design is needed

The CAP Theorem

The CAP theorem states that in any distributed data system, you can only guarantee two out of three: Consistency, Availability, and Partition Tolerance.

• SQL databases often prioritize consistency and availability but may struggle with partition tolerance at scale.

• NoSQL databases are typically designed for partition tolerance and either consistency or availability, depending on configuration. For example, MongoDB can be tuned for consistency and partition tolerance (CP) or availability and partition tolerance (AP), but not all three simultaneously

The choice between consistency and availability depends on the application’s requirements.

Banking apps cannot risk errors in account balances, so it prioritizes consistency. Apps focused on user experience and uptime, like Rapido and Amazon, prioritize availability, accepting minor inconsistencies that will be resolved later.

• Conclusion

  Choosing between SQL and NoSQL depends on your application's needs:

  • Use SQL for structured data, complex relationships, and transactional integrity (e.g., payments, inventory).

  • Use NoSQL for scalability, flexibility, and handling unstructured or high-velocity data (e.g., product catalogs, real-time analytics).

Modern platforms like Flipkart, Netflix, and Uber often use a hybrid approach, leveraging both SQL and NoSQL databases to balance consistency, scalability, and performance across different parts of their systems