Bhavesh vaswani on Instagram: "Database scaling ensures your system can handle millions of users and queries without slowing down or crashing. ⸻ 1️⃣ Read Replicas • Copies your database to multiple nodes to handle heavy read traffic. • Example: Like multiple ATMs so everyone can withdraw money at once. ⸻ 2️⃣ Sharding / Partitioning • Splits your database into smaller pieces (shards) to store data efficiently. • Example: Users A–E in one shard, F–J in another for faster queries. ⸻ 3️⃣ Caching • S

Rajan Walia on Instagram: "3 Backend Projects every Student should make in 2025 Coding Programming Node.js Express.js NestJS JavaScript TypeScript Python Django Flask FastAPI Java Spring Boot C# . NET Golang Ruby Ruby on Rails PHP Laravel Backend Backend Development Backend Engineer API Development REST API GraphQL gRPC Microservices Monolith Serverless System Design Database SQL NoSQL MySQL PostgreSQL MongoDB Redis Cassandra DynamoDB ORM Prisma Sequelize Hibernate Authentication Authorization J