Data storage systems
🧱 1. Operational Databases (OLTP Systems) These are the classic, transactional databases used for daily operations — the ones we usually just call “databases.” Purpose: Store and manage live data for apps or systems. Data Type: Structured (tables, rows, columns). Examples: Relational: MySQL, PostgreSQL, Oracle, SQL Server NoSQL (non-relational): MongoDB, Cassandra, Redis Used for: e-commerce transactions, banking systems, CRM apps, etc. 🧠2. Analytical Databases (OLAP Systems) These include data warehouses — optimized for analysis and reporting, not transactions. Examples: Snowflake, Amazon Redshift, Google BigQuery, Azure Synapse 🌊 3. Data Lakes Hold raw or unstructured data (logs, images, sensor data, etc.). Examples: Amazon S3 (as a lake), Azure Data Lake Storage, Google Cloud Storage Now, here are other important types beyond those three 👇 🗂️ 4. Data Lakehouse A hybrid between a data warehouse and a data lake . Can handle structured + unst...