Notes

DATA STORAGE
- The inventory data will be stored in a database optimized for fast retrieval either a relational database like PostgreSQL or a non-relational database like MongoDB. Or, a database that is more suitable for large-scale data storage and retrieval like ElsaticSearch.

TECHNIQUES
- Pagination which is the process of dividing search results into manageable chunks or pages, in turn reducing the amount of time and data gotten from the storage unit.
- Asynchronous loading will be used to load assets or data without affecting the main thread, e.g. fetching data from an API using a useEffect hook.
- Lazy loading will be used to defer the loading of resources until they are needed, e.g. the deferment of other parts of the web until it's needed by the webpage.
- Indexing will be used coupled with the traditional database if used. It helps to speed up search queries and retrievals on the database.
- Caching strategies will be used to keep frequently assessed data or search in-memory like Redis, for faster data retrieval.

TRADE-OFFS
- The first tradeoff I'll consider is cost. Some services like Elasticsearch and Redis can increase the cost of production.
- Complexity is another factor I'll consider. Some optimization may introduce some complex steps or processes to the system's architectural design making the maintenance more challenging, in turn requiring more technical expertise.
- Scalability is required if the application is built with the aim of making it grow. some chosen solutions might make it hard to properly and seamlessly scale an application according to its user base.