Database indexing is the practice of creating data structures that let a database find rows quickly without scanning a whole table. It speeds up reads at the cost of extra storage and slower writes.
Data modeling is designing how data is structured, named and related, so it can be stored efficiently and queried correctly. It applies to both application databases and analytics platforms.
SQL (Structured Query Language) is the standard language for defining, querying and changing data in relational databases. It is used to filter, join, aggregate and update rows stored in tables.
Caching stores copies of frequently used data in a faster location so future requests can be served without repeating slow work. That slow work might be a database query, a computation or a network call.
An ORM (object-relational mapper) is a library that maps database tables to objects in application code. Developers can read and write data with their programming language instead of writing raw SQL for every query.
The difference is the data model: SQL databases keep related tables under a fixed schema, and NoSQL databases use flexible documents, key-value pairs or graphs. SQL is strongest at joins and transactions; NoSQL often scales out more easily.
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