Modern digital applications demand the ability to process massive numbers of transactions while maintaining reliability, scalability, and responsiveness across geographically distributed infrastructures. Traditional monolithic architectures often struggle to support the throughput requirements of large-scale distributed systems due to tight coupling between components, limited horizontal scalability, and the difficulty of isolating failures within a single codebase. As workloads grow and user bases expand globally, these limitations become increasingly evident in areas such as transaction latency, system availability, and deployment agility. Distributed microservices architectures offer a viable alternative by decomposing applications into smaller, independently deployable services that communicate through lightweight APIs or event-driven messaging systems. This architectural paradigm enables organizations to scale services horizontally, optimize resource utilization, and process transactions concurrently across distributed environments. In such systems, each microservice typically manages its own data store and business logic, allowing for flexible scaling and improved resilience. This paper examines the architectural principles, distributed transaction models, and performance optimization strategies that enable high-throughput transaction processing in microservices environments. The study reviews existing research on distributed transaction processing systems, including distributed OLTP platforms and main-memory databases that reduce I/O bottlenecks and improve transaction latency. It also analyzes microservice orchestration patterns and coordination mechanisms that enable reliable transaction management across multiple services. Particular attention is given to techniques such as data partitioning, asynchronous messaging, event-driven communication, and Saga-based transaction coordination, which collectively help maintain data consistency without sacrificing system performance. Through the analysis of existing systems, architectural patterns, and prior research studies, the paper highlights approaches that significantly improve transaction throughput while preserving fault tolerance, service autonomy, and data consistency in complex distributed computing environments.