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.
A data warehouse is a central database built for analysis, holding cleaned, structured data from many systems. Analysts and BI tools query it for reports, dashboards and planning.
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.
The backend is the server-side part of an application that users do not see. It holds business logic, data storage, integrations and security, and serves the front end and other systems through APIs.
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.
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.
A NoSQL database stores and retrieves data without the fixed tables and relations of traditional SQL systems. It uses documents, key-value pairs, wide columns or graphs, and is often built to scale horizontally.
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