This content originally appeared on DEV Community and was authored by Aditi Sharma

Database vs Data Warehouse 🗄️

Today I explored the key differences between Databases and Data Warehouses — two pillars of data management.

🔹 Database
• Designed for day-to-day operations (OLTP – Online Transaction Processing).
• Stores current data (e.g., banking, e-commerce).
• Optimized for fast reads/writes.

🔹 Data Warehouse
• Designed for analytics & reporting (OLAP – Online Analytical Processing).
• Stores historical + integrated data from multiple sources.
• Optimized for complex queries & aggregations.

📌 Key Difference in One Line:

Database → Running the business.
Data Warehouse → Analyzing the business.

⚡ Fun Fact: The term Data Warehouse was first coined in the 1980s and became the backbone of business intelligence systems.

DataAnalytics #Database #DataWarehouse #100DaysOfCode #Python

This content originally appeared on DEV Community and was authored by Aditi Sharma

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