1️⃣ What is a Database?
A: A structured collection of data stored electronically for efficient retrieval and management. Examples: MySQL (relational), MongoDB (NoSQL), PostgreSQL (advanced relational with JSON support)—essential for apps handling user data in 2025's cloud era.
2️⃣ Difference between SQL and NoSQL
⦁ SQL: Relational with fixed schemas, tables, and ACID compliance for transactions (e.g., banking apps).
⦁ NoSQL: Flexible schemas for unstructured data, scales horizontally (e.g., social media feeds), but may sacrifice some consistency for speed.
3️⃣ What is a Primary Key?
A: A unique identifier for each record in a table, ensuring no duplicates and fast lookups. Example: An auto-incrementing
id in a Users table—enforces data integrity automatically.4️⃣ What is a Foreign Key?
A: A column in one table that links to the primary key of another, creating relationships (e.g., Orders table's
user_id referencing Users). Prevents orphans and maintains referential integrity.5️⃣ CRUD Operations
⦁ Create:
INSERT INTO table_name (col1, col2) VALUES (val1, val2);⦁ Read:
SELECT * FROM table_name WHERE condition;⦁ Update:
UPDATE table_name SET col1 = val1 WHERE id = 1;⦁ Delete:
DELETE FROM table_name WHERE condition; These are the core for any data manipulation—practice with real datasets!
6️⃣ What is Indexing?
A: A data structure that speeds up queries by creating pointers to rows. Types: B-Tree (for range scans), Hash (exact matches)—but over-indexing can slow writes, so balance for performance.
7️⃣ What is Normalization?
A: Organizing data to eliminate redundancy and anomalies via normal forms: 1NF (atomic values), 2NF (no partial dependencies), 3NF (no transitive), BCNF (stricter key rules). Ideal for OLTP systems.
8️⃣ What is Denormalization?
A: Intentionally adding redundancy (e.g., duplicating fields) to boost read speed in analytics or read-heavy apps, trading storage for query efficiency—common in data warehouses.
9️⃣ ACID Properties
⦁ Atomicity: Transaction fully completes or rolls back.
⦁ Consistency: Enforces rules, leaving DB valid.
⦁ Isolation: Transactions run independently.
⦁ Durability: Committed data survives failures.
Critical for reliable systems like e-commerce.
🔟 Difference between JOIN types
⦁ INNER JOIN: Returns only matching rows from both tables.
⦁ LEFT JOIN: All from left table + matches from right (NULLs for non-matches).
⦁ RIGHT JOIN: All from right + matches from left.
⦁ FULL OUTER JOIN: All rows from both, with NULLs where no match.
Visualize with Venn diagrams for interviews!
1️⃣1️⃣ What is a NoSQL Database?
A: Handles massive, varied data without rigid schemas. Types: Document (MongoDB for JSON-like), Key-Value (Redis for caching), Column (Cassandra for big data), Graph (Neo4j for networks).
1️⃣2️⃣ What is a Transaction?
A: A logical unit of multiple operations that succeed or fail together (e.g., bank transfer: debit then credit). Use
BEGIN, COMMIT, ROLLBACK in SQL for control.1️⃣3️⃣ Difference between DELETE and TRUNCATE
⦁ DELETE: Removes specific rows (with WHERE), logs each for rollback, slower but flexible.
⦁ TRUNCATE: Drops all rows instantly, no logging, resets auto-increment—faster for cleanup.
1️⃣4️⃣ What is a View?
A: Virtual table from a query, not storing data but simplifying access/security (e.g., hide sensitive columns). Materialized views cache results for performance in read-only scenarios.
1️⃣5️⃣ Difference between SQL and ORM
⦁ SQL: Raw queries for direct DB control, powerful but verbose.
⦁ ORM: Abstracts DB as objects (e.g., Sequelize in JS, SQLAlchemy in Python)—easier for devs, but can hide optimization needs.
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