Attainu Project

Restaurant Review Web Application

Stage 1 (out of 3) project

Live project link

GitHub code link

What are we trying to build?

We had built a Restaurant Review website application – to help users choose a restaurant to visit by going through the comments and reviews posted by other users. The user can also comment, review and upload photos of a restaurant.

Why did we choose to work on this?

The reason why we selected this project is that it involves a fair amount of database operations like creating, updating, deleting records and it also involves uploading and deleting files from the server.

It also gave us an idea of how applications like Zomato and Swiggy work on a big scale and what kind of challenges one faces when building these kinds of applications.

Technologies used and why?

  • We have used bootstrap at frontend since it allows us to create responsive UI in less time. It is useful in making responsive, mobile-first front-end web development and it also contains CSS- and JavaScript-based design templates for typography, forms, buttons, navigation and other interface components.
  • Node.js is a server-side platform built on google chrome’s javascript V8 engine for easily building fast and scalable network applications. Node.js uses an event-driven, non-blocking I/O model that makes it lightweight and efficient, perfect for data-intensive real-time applications that run across distributed devices.
  • For the database, we have used MongoDB which is a NoSQL database. One of the best things about MongoDB is that there are no restrictions on schema design. It allows using an unstructured query language. Besides that, the main benefit it has over MySQL is its ability to handle large unstructured data.

Future scope of improvement?

In future we would like to include –

  • Social media authentication like facebook, twitter, google etc
  • Shareable links which user can use to share the restaurant with others.
  • Auto detect the location for displaying the restaurant location.
  • Face emotion recognition for Rating automation.
  • Integrate this application with virtual assistant like Alexa, Google Home etc


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