Distributed Transactions with 2-Phase Commit | Data Consistency in Microservices

Welcome back to our System Design Series! In this episode, we dive deep into one of the most fundamental concepts in distributed systems: Distributed Transactions starting with the 2-Phase Commit Protocol (2PC). When working with microservices architecture, ensuring data consistency across services like Inventory, Payment, and Order becomes a challenge. What happens when one service succeeds but another fails? That’s where distributed transactions come in and 2PC is the basic protocol to coordinate them. 🔍 What You'll Learn in This Video: Why data consistency is hard in microservices Real-world example: placing an order across Inventory, Payment, and Order services The need for distributed transactions in microservice-based systems 🔄 What is 2-Phase Commit and how it works Phase 1: Prepare Phase Phase 2: Commit Phase ✅ How 2PC ensures atomicity across distributed services ⚠️ Major problems with 2PC Blocking resources Single point of failure Tight coupling and synchronous communication Poor fault tolerance 🧠 When does 2PC still make sense? 💡 What's next after 2PC a glimpse into 3-Phase Commit, Saga Pattern, and Outbox Pattern 📌 This video is essential for backend engineers, architects, and anyone serious about learning system design and microservices best practices. 🔔 Subscribe for more deep dives into Microservices, System Design, and Cloud Architecture. 👍 Like | 💬 Comment | 📤 Share #SystemDesign #DistributedSystems #2PC #Microservices #DistributedTransactions #Atomicity #Consistency #BackendEngineering #SoftwareArchitecture #SagaPattern #OutboxPattern #CloudNative #DesignPatterns #TechEducation #RateLimiting #Throttling #Microservices #SystemDesign #DistributedSystems #NetflixArchitecture #TechExplained #CloudArchitecture #BackendEngineering #Scalability To check out more on the tutorials Topic wise you can follow below links Links: Please do checkout other tutorial videos also if required: Spring Framework: https://www.youtube.com/playlist?list=PLOktGWstEbloSPMJ1unePUM6RBRq5PITf DevOps: https://www.youtube.com/playlist?list=PLOktGWstEbloOXfYeErrQzmEMev9kMiTR Java Design Patterns: https://www.youtube.com/playlist?list=PLOktGWstEblrsAq3NBW-3IvKXUG12g4YI Java 8 Features: https://www.youtube.com/playlist?list=PLOktGWstEblq7U723DhM22BWPTe7Juy3v Core Java Complete Tutorial: https://www.youtube.com/playlist?list=PLOktGWstEblosEXd96yj4pdN8OCX7cDOu Interview Preparation for Java: https://www.youtube.com/playlist?list=PLOktGWstEblqGRuD7oUb6mJWQRs5MCZ_a Python: https://www.youtube.com/playlist?list=PLOktGWstEblpsjnKH7qAnCgPa6k224zDw Linux: https://www.youtube.com/playlist?list=PLOktGWstEblqOSZ9ikDYHunYfb7D8beHq Please do LIKE, Share and SUBSCRIBE Thank You Database Sharding, Sharding Explained, Data Hotspot, Optimal Sharding Key, Database Scaling, Cardinality in Sharding, Frequency in Sharding, Monotonic Change in Sharding, Database Architecture, System Design, Scalable Databases, Backend Architecture, Sharding Key Selection, Avoiding Data Hotspots, Hash Based Sharding, Database Performance, Sharding Strategies, Distributed Databases, High Scalability Databases, Backend Engineering, System Design for Beginners, Database Optimization, Sharding Mistakes, Database Partitioning, Black Friday Scaling, Auto Increment ID Sharding, Range Based Sharding, Hash Based Distribution, Composite Sharding Key, Handling Hotspots, Microservices Database Design