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🎁Store key-value pairs in memory for ultra-fast access and pub/sub messaging.
Store flexible JSON-like documents with dynamic schemas and indexing.
Use SQL to manage structured data with ACID compliance and joins.
Run complex queries, CTEs, and geospatial analysis with powerful extensions.
Pick Redis for caching, MongoDB for NoSQL, MySQL/PostgreSQL for relational data.
Install via package manager, Docker, or cloud service and set up access.
Use tables (SQL) or collections (NoSQL) to structure your data.
Use SQL or query language to fetch, filter, and index data efficiently.
Connect to backend apps and scale with replication, sharding, or clustering.
// Redis (Node.js)
const redis = require('redis');
const client = redis.createClient();
client.set('key', 'value');
// MongoDB (Node.js)
const { MongoClient } = require('mongodb');
const client = new MongoClient(uri);
await client.db("mydb").collection("users").insertOne({ name: "Tanu" });
// MySQL (SQL)
SELECT * FROM users WHERE email = 'tanu@example.com';
// PostgreSQL (SQL)
SELECT name FROM users WHERE created_at > NOW() - INTERVAL '7 days';
Use Redis to store user sessions and reduce database load.
Use MongoDB for dynamic schemas in content, logs, or IoT data.
Use MySQL for banking, e-commerce, and ERP systems with ACID guarantees.
Use PostgreSQL for analytics, reporting, and geospatial queries.
Explore Redis / MongoDB / MySQL / PostgreSQL’s ecosystem and find the tools, platforms, and docs to accelerate your workflow.
Common questions about Redis / MongoDB / MySQL / PostgreSQL’s capabilities, usage, and ecosystem.