💰 Transactions & Sagas in Distributed Systems

Welcome back to The Code Hut Distributed Systems series! In this post, we’ll discuss how to handle transactions that span multiple services or nodes — a common challenge in distributed systems.

The Problem with Distributed Transactions

In a single database, transactions are simple: ACID guarantees ensure consistency. But in a distributed system:

• Multiple services may need to update different databases
• Network failures can occur mid-transaction
• Traditional two-phase commit (2PC) can be slow and complex

The Saga Pattern

The Saga pattern is a way to manage distributed transactions as a series of local transactions:

• Each service performs a local transaction
• If a step fails, compensating transactions undo previous steps
• Ensures eventual consistency without blocking resources

Example in Java (Simplified)

Imagine an e-commerce system where a transaction involves three services:

• Order Service
• Payment Service
• Inventory Service

// Simplified Saga pseudocode
try {
    orderService.createOrder(order);
    paymentService.chargeCustomer(order);
    inventoryService.reserveStock(order);
} catch (Exception e) {
    // Compensating actions in case of failure
    inventoryService.releaseStock(order);
    paymentService.refundCustomer(order);
    orderService.cancelOrder(order);
}

Benefits of Sagas

• ✅ No need for distributed locks across services
• ✅ Scales well with microservices
• ✅ Supports eventual consistency

Next in the Series

In the next post, we’ll explore Fault Tolerance & Reliability, including patterns like replication, retries, and idempotency in distributed Java systems.

Label for this post: Distributed Systems