End to End E-Commerce website for big data

1. ISM 6562-
BIG DATA E-COMMERCE PROJECT
Submitted by :
Poonam Krishna
Shreyas Dalvi
Yashjeet Singh

2. COMPONENTS
NoSQL DB : MongoDB
Search system : Amazon Elasticsearch Service with Kibana
Cache system : Redis Cache
CDN: Amazon CloudFront
Application Server: Node.js
Deployment platform: Heroku

3. ARCHITECTURE
Cache system App Server
CDN User
No SQL DB Search System

4. MONGODB
Key Benefits of Mongo DB are:
1) Scaling
2) Flexible Schema
3) Real Time Analytics
- JSON Data
- Used Robo 3T to load data in the database.
- Product data scrapped from Amazon.com using web scraper.
- Mongoose driver for connecting Node.js and MongoDB.
- User signup profile and orders created via website is also stored in DB

5. ELASTIC SEARCH
Utilized Amazon ElasticSearch Service to implement search functionality.
1. 750 hours per month of a single-AZ t2.small.elasticsearch instance.
2. 10GB per month of optional EBS storage (Magnetic or General Purpose).
Used Kibana to create and upload document indexes.
Used http-aws-es and aws-sdk packages to make elasticsearch-js compatible with Amazon ES.

6. REDIS CACHE
Used Redis service provided by REDIS LAB for implementing cache functionality.
High throughput and low latency to support scalable services.
Created instance at Redis lab to use it as a service.

7. NODE.JS
Node JS to develop the front end web application.
Node JS is connected to mongo Db, ElasticSearch and
Redis Cache.
Used PHPStorm as the development tool for coding.

8. CDN: CLOUDFRONT
- Used Cloudfront for caching of static web contents
- Deliver high bandwidth contents to users globally
- Reduce latency in system
- Scaling

9. WEB DEPLOYMENT
Used Heroku to deploy node js application.
Free service with benefits of instant deployment.
Convenient Scaling.
Supports various plugins for 3rd party tools.
Heroku Dashboard and Heroku CLI helps in app management.
500 MB of free size to host the application.