Food Delivery Database

-- Create Database
CREATE DATABASE food_delivery_system;

USE food_delivery_system;

• 1Manages customers and restaurants.
• 2Processes food orders.
• 3Tracks deliveries.
• 4Handles payments.
• 5Provides real-time order updates.

• 1Customers.
• 2Restaurants.
• 3Menu Items.
• 4Orders.
• 5Order Items.
• 6Payments.
• 7Delivery Partners.
• 8Order Tracking.

• 1Stores customer information.
• 2Maintains delivery addresses.
• 3Tracks order history.
• 4Supports customer accounts.

• 1Stores restaurant details.
• 2Tracks operational status.
• 3Maintains contact information.
• 4Supports restaurant onboarding.

• 1Stores food item information.
• 2Maintains pricing details.
• 3Tracks item availability.
• 4Links items to restaurants.

• 1Stores customer orders.
• 2Tracks order status.
• 3Maintains order totals.
• 4Supports order history.

• 1Stores ordered food items.
• 2Tracks quantities.
• 3Maintains pricing snapshots.
• 4Supports invoice generation.

• 1Stores payment transactions.
• 2Tracks payment status.
• 3Supports refunds.
• 4Maintains billing history.

• 1Stores delivery executive details.
• 2Tracks delivery assignments.
• 3Maintains availability status.
• 4Supports logistics management.

• 1Tracks order progress.
• 2Stores status updates.
• 3Maintains delivery timelines.
• 4Supports real-time tracking.

• 1One Customer → Many Orders.
• 2One Restaurant → Many Menu Items.
• 3One Order → Many Order Items.
• 4One Order → One Payment.
• 5One Delivery Partner → Many Deliveries.
• 6One Order → Many Tracking Updates.

• 1Customer places order.
• 2Restaurant accepts order.
• 3Food preparation starts.
• 4Delivery partner assigned.
• 5Order picked up.
• 6Order delivered.
• 7Customer feedback submitted.

• 1Pending.
• 2Accepted.
• 3Preparing.
• 4Ready for Pickup.
• 5Out for Delivery.
• 6Delivered.
• 7Cancelled.

• 1Restaurant Sales Report.
• 2Delivery Performance Report.
• 3Customer Order History.
• 4Daily Revenue Report.
• 5Popular Food Items Report.

• 1Real-time order management.
• 2Improved customer experience.
• 3Efficient delivery tracking.
• 4Automated payment processing.
• 5Scalable food delivery operations.

• 1Customers order food online.
• 2Restaurants manage menu items.
• 3Delivery partners deliver orders.
• 4Payment gateways process transactions.
• 5Businesses track order statuses in real time.
• 6Food delivery platforms generate sales reports.
• 7SaaS products use Food Delivery Database in services, dashboards, background jobs, and API workflows.
• 8ERP and banking systems apply Food Delivery Database with validation, logging, review, and rollback plans.
• 9E-commerce and healthcare platforms use Food Delivery Database carefully because reliability and data correctness matter.

• 1A Sql program first evaluates the surrounding context, then applies the Food Delivery Database rules to the current data.
• 2The important mental model is input, transformation, result, and failure path.
• 3In production, the same flow usually sits inside a larger layer such as a controller, service, repository, job, or UI component.

• 1Choose the simplest implementation first, then measure real workloads.
• 2Watch for repeated work inside loops, unnecessary allocations, and slow I/O in hot paths.
• 3Prefer clear data structures and stable APIs before micro-optimizing syntax.

• 1Treat external input as untrusted until it is validated.
• 2Avoid hardcoded secrets and never print sensitive values in examples or logs.
• 3Use established libraries for authentication, encryption, parsing, and database access.

• 1Not tracking order status changes.
• 2Ignoring delivery partner assignments.
• 3Allowing menu items without restaurant references.
• 4Mixing order and payment information in one table.
• 5Failing to maintain order history.
• 6Skipping the small working example before adding framework code.
• 7Ignoring null, empty, duplicate, and boundary inputs.
• 8Mixing business logic, input handling, and output formatting in one place.
• 9Using broad error handling that hides the real failure.
• 10Forgetting to test the behavior after refactoring.

• 1Maintain complete order lifecycle tracking.
• 2Use foreign key relationships.
• 3Store payment transactions separately.
• 4Track delivery partner assignments.
• 5Implement status audit logs.
• 6Optimize real-time order queries.
• 7Start with clear requirements and one minimal working example.
• 8Use meaningful names that explain business intent.
• 9Keep examples small enough to debug line by line.
• 10Validate input at every trust boundary.
• 11Handle errors explicitly and preserve useful context.
• 12Prefer simple control flow over deeply nested logic.
• 13Separate domain logic from I/O and framework code.
• 14Write tests for normal, boundary, and failure cases.
• 15Review security assumptions before production use.
• 16Measure performance before optimizing.
• 17Document non-obvious decisions close to the code or in project notes.
• 18Use official documentation when behavior is version-specific.
• 19Keep dependencies current and remove unused code.
• 20Avoid hardcoded secrets, credentials, and environment-specific paths.

• 1Beginner: rewrite the example with different names and values.
• 2Intermediate: add validation and handle one expected failure case.
• 3Advanced: place Food Delivery Database inside a small service-style design with tests.

• 1Build a small Sql console feature that demonstrates Food Delivery Database.
• 2Accept input, process it with the concept, print a clear result, and handle invalid input.
• 3Add a README note explaining the design choice and two edge cases you tested.

• 1If the program does not compile, check spelling, imports, braces, and file/class names first.
• 2If output is unexpected, print intermediate values and verify each branch of the logic.
• 3If the design feels complex, reduce it to the smallest working example and add pieces back one at a time.

• 1Practice Food Delivery Database with a second example from a business domain such as inventory, payroll, banking, or e-commerce.
• 2Review related Sql topics that cover data flow, error handling, testing, and clean design.
• 3Compare your solution with official documentation and simplify anything you cannot explain clearly.

• 1Customers order food online.
• 2Restaurants manage menu items.
• 3Delivery partners deliver orders.
• 4Payment gateways process transactions.
• 5Businesses track order statuses in real time.
• 6Food delivery platforms generate sales reports.
• 7SaaS products use Food Delivery Database in services, dashboards, background jobs, and API workflows.
• 8ERP and banking systems apply Food Delivery Database with validation, logging, review, and rollback plans.
• 9E-commerce and healthcare platforms use Food Delivery Database carefully because reliability and data correctness matter.

• 1Not tracking order status changes.
• 2Ignoring delivery partner assignments.
• 3Allowing menu items without restaurant references.
• 4Mixing order and payment information in one table.
• 5Failing to maintain order history.
• 6Skipping the small working example before adding framework code.
• 7Ignoring null, empty, duplicate, and boundary inputs.
• 8Mixing business logic, input handling, and output formatting in one place.
• 9Using broad error handling that hides the real failure.
• 10Forgetting to test the behavior after refactoring.
• 11Adding clever code that future maintainers will struggle to read.
• 12Not checking performance on realistic input sizes.

• 1Maintain complete order lifecycle tracking.
• 2Use foreign key relationships.
• 3Store payment transactions separately.
• 4Track delivery partner assignments.
• 5Implement status audit logs.
• 6Optimize real-time order queries.
• 7Start with clear requirements and one minimal working example.
• 8Use meaningful names that explain business intent.
• 9Keep examples small enough to debug line by line.
• 10Validate input at every trust boundary.
• 11Handle errors explicitly and preserve useful context.
• 12Prefer simple control flow over deeply nested logic.
• 13Separate domain logic from I/O and framework code.
• 14Write tests for normal, boundary, and failure cases.
• 15Review security assumptions before production use.
• 16Measure performance before optimizing.
• 17Document non-obvious decisions close to the code or in project notes.
• 18Use official documentation when behavior is version-specific.
• 19Keep dependencies current and remove unused code.
• 20Avoid hardcoded secrets, credentials, and environment-specific paths.
• 21Log operational events without exposing sensitive data.
• 22Design examples so learners can safely modify and rerun them.
• 23Prefer maintainability over short-term cleverness.