Editing Openai/692e1a61-9f08-800b-89a7-b2d4c506df31 (section)

==== 3. Why would a company choose NoSQL? ====

Common business/technical motivations:

===== 1) Massive scale and high availability needs =====
* Global consumer apps, social networks, IoT platforms, ad-tech, large e-commerce — all often face: - Billions of records - Very spiky traffic - Multi-region deployments
* NoSQL can provide simpler scaling and replication patterns, and built-in sharding.

===== 2) Rapidly evolving products / data models =====
* Startups iterating quickly on product features
* Companies integrating many third-party data sources with inconsistent schemas
* APIs that frequently add/remove fields

NoSQL’s flexible schema reduces migration pain and allows quicker iteration.

===== 3) Specific data models that fit better than relational =====
* Document-oriented domains: content management, user profiles, application settings
* Time series and event data: logs, metrics, sensor data (often wide-column or time-series DBs)
* Relationship-heavy domains: social graphs, recommendation systems, fraud detection (graph DBs)

Using a data model aligned with the use case can simplify code and improve performance.

===== 4) Microservices and polyglot persistence =====

Companies increasingly use polyglot persistence:
* Different services use the storage technology best suited to their needs
* Example: - Core billing and financial transactions: relational DB for ACID guarantees - Session storage, cache, and rate-limiting: key-value store (Redis) - Product catalog and user profiles: document store - Analytics backend: columnar or data warehouse

NoSQL is often the right choice for some subset of those services.

===== 5) Cost and operational considerations (sometimes) =====

Managed NoSQL services (e.g., DynamoDB, Firestore, Cosmos DB, MongoDB Atlas, etc.) can:
* Offload much of the operational burden (backups, replication, scaling)
* Offer pay-as-you-go pricing that maps to request volume / storage
* Reduce the need for specialized DBA work in some contexts

This is not universally cheaper, but for certain traffic patterns and staffing constraints, it can be very attractive.