The goal of this project is to study JPA Batch Processing (i.e., inserting, updating, or deleting a set of records in a single command) and JPA Locking.

Examples of applying pessimistic and optimistic concurrency control with AWS DynamoDB.

🔒 Implement distributed locking for .NET background jobs to prevent duplicate execution and ensure data consistency across multiple application instances.

High-performance EntityFrameworkCore.Sqlite extension for concurrent reads and writes. Fix EFCore SQLite "database is locked" and "busy" errors with 10x faster bulk inserts and parallel read scaling. The definitive thread-safe solution for SQLite performance and concurrency in dotnet

A project to master database transaction management and isolation levels in PostgreSQL by investigating and reproducing ACID anomalies including Lost Update, Non-Repeatable Reads, Phantom Reads, and Deadlocks.

This Repository Contains Implementation for Database Locking with Spring Data JPA and Test It Using JMeter to Send Concurrent Requests to Test Optimistic Locking

A robust .NET library for distributed locking of background jobs across multiple application instances, supporting Hangfire, Coravel, and custom implementations with SQL Server, PostgreSQL, and Redis backends.

Airline Checkin System APIs

A Spring Boot application demonstrating optimistic and pessimistic database locking to handle concurrent transactions, prevent data inconsistencies, and ensure reliable data integrity in multi-user systems.

Laravel 12 API for slot booking with Redis caching (5-15s TTL), idempotency middleware, and MySQL transaction locks to prevent overselling. Implements hold/confirm/cancel workflow with cache stampede protection.