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

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

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.

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.

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.