Introduction to Databases

Lesson content

Introduction to Databases MongoMart experience path: This topic is taught through the same MongoMart e-commerce system used throughout the course. Shared database // Core MongoMart collections customers: { _id, name, email, addresses[], createdAt } products: { _id, sku, name, categoryId, price, attributes, stock } carts: { _id, customerId, items[], expiresAt } orders: { _id, orderNo, customerId, items[], status, total, orderedAt } inventory: { _id, sku, available, reserved, warehouseId } payments: { _id, orderId, providerRef, status, amount } notifications: { _id, customerId, type, payload, sentAt } Beginner foundation Define Introduction to Databases, identify what problem it solves, and run the smallest working example before adding abstraction. Real-world scenario MongoMart stores customers, products, carts, orders, inventory, payments, and notifications as related document workflows. Practical example use mongomart db.customers.findOne({ email: "asha@example.com" }) Intermediate reasoning Predict the exact documents read or changed. Test missing fields, nulls, duplicates, empty arrays, and boundary values. Validate the result with a second query or assertion. Advanced production use Measure behavior with realistic cardinality and concurrency. Add indexes or distributed features only after identifying the actual access pattern and failure mode. 10-year experience perspective Define ownership, invariants, naming, compatibility, and how the model will evolve before selecting a MongoDB feature. Review checklist Correctness and atomicity Schema evolution and backward compatibility Performance and capacity evidence Security and privacy Failure recovery, monitoring, and ownership Easy example Find one customer by email and return only the fields needed by the screen. db.customers.findOne( { email: "asha@example.com" }, { name: 1, email: 1, status: 1 } ) How to verify the easy example Run it with representative input. Confirm the expected output. Try one missing, invalid, or boundary value. Advanced example Aggregate completed orders by customer, rank revenue, and verify the access pattern with execution statistics. db.orders.aggregate([ { $match: { status: "completed" } }, { $group: { _id: "$customerId", revenue: { $sum: "$total" } } }, { $setWindowFields: { sortBy: { revenue: -1 }, output: { revenueRank: { $denseRank: {} } } } }, { $limit: 20 } ]).explain("executionStats") Advanced review Explain the tradeoffs and assumptions. Test failure, scale, security, and recovery behavior. Capture evidence from tests, execution plans, logs, or review output. Additional practical guidance Introduction to Databases production detail Define ownership, invariants, naming, compatibility, and how the model will evolve before selecting a MongoDB feature. Required evidence A repeatable setup and test case The expected successful result One failure or edge case Relevant explain, profiler, log, or monitoring output A rollback or recovery approach