An open API service indexing awesome lists of open source software.

https://github.com/antoniakras/retail-transactions-system

Java web app with Servlets, JDBC, and SQL, deployed on Tomcat. Includes REST-style endpoints and complex SQL queries.
https://github.com/antoniakras/retail-transactions-system

apache-tomcat backend-development database html java javascript jdbc rest-api servlets sql webapp

Last synced: about 1 month ago
JSON representation

Java web app with Servlets, JDBC, and SQL, deployed on Tomcat. Includes REST-style endpoints and complex SQL queries.

Awesome Lists containing this project

README

          

# Retail-Transactions-System – Java Servlets & SQL Backend Application

## 🚀 About
This project demonstrates the design and implementation of a **Java web application using Servlets, JDBC, and SQL**, deployed on an **Apache Tomcat container**. It follows a **REST-style architecture**, exposing endpoints for data management and interaction with a relational database.

---

## 📂 Features
- **Java Servlets backend** – request handling and business logic
- **REST-style API** – structured endpoints for CRUD operations
- **Relational database integration** – via JDBC and SQL
- **Tricky SQL queries** – involving joins, aggregations, nested queries, and constraints
- **Deployment** – configured and run in an **Apache Tomcat servlet container**

---

## 🛠️ Setup & Run

1. Install [Apache Tomcat](https://tomcat.apache.org/) (tested with v9+).
2. Clone the repository:
```bash
git clone git@github.com:antoniakras/retail-transactions-system.git
cd retail-transactions-system
3. Deploy the .war file or the compiled classes to your Tomcat webapps/ directory.

4. Start Tomcat and access the application via: http://localhost:8080/hy360\

---

🔍 Queries Highlight

* The project goes beyond basic CRUD and demonstrates:

* Multi-table JOINs to fetch aggregated information

* Nested subqueries for filtering and reporting

* Group by + Having for advanced analytics

* Referential integrity checks with constraints

* Performance-aware query design