Self-Hosted Saga Orchestrators — Temporal vs Camunda vs Cadence 2026

The saga pattern solves the problem of distributed transactions in microservices — when a business process spans multiple services, each with its own database, traditional ACID transactions are impossible. Instead, sagas break the process into a sequence of local transactions, each with a corresponding compensation action that undoes it if a later step fails.

While the saga pattern can be implemented manually in application code, saga orchestrators provide a dedicated infrastructure layer that coordinates the steps, tracks state, handles retries, and executes compensations automatically. This guide compares three self-hosted saga orchestration platforms: Temporal, Camunda, and Cadence.

Why Self-Host Saga Orchestration?

Distributed transaction coordination is too critical to outsource to a SaaS provider. When your payment processing, inventory management, and notification services all depend on saga coordination, any external outage cascades into business disruption. Self-hosting eliminates this dependency.

Saga orchestrators also store the complete state of every running workflow. This includes business data, execution history, and timing information that may be subject to data residency requirements. Running the orchestrator on your own infrastructure ensures that workflow state never leaves your control.

For teams already using workflow orchestration for general-purpose automation, our workflow engine comparison covers the broader landscape. If you’re building CQRS systems that need saga coordination, our CQRS platform guide provides the event sourcing foundation. And for coordinating distributed state across saga participants, our distributed locking guide covers the synchronization layer.

Temporal: Durable Execution for Distributed Systems

Temporal is an open-source durable execution platform that makes building reliable distributed applications simple. Rather than writing complex retry, timeout, and state management logic, you write normal code and Temporal guarantees it runs to completion, even if services crash or networks fail.

Key features:

• Code-first workflow definition — write workflows in Go, Java, Python, TypeScript, or .NET
• Automatic retries with configurable backoff policies
• Durable timers — sleep for days or weeks without consuming resources
• Built-in saga pattern support with automatic compensation
• Event sourcing for workflow state — full audit trail of every execution
• Horizontal scalability with automatic load balancing
• Web UI for workflow monitoring and debugging

Docker Compose Configuration

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services:
  temporal:
    image: temporalio/auto-setup:latest
    container_name: temporal
    restart: unless-stopped
    ports:
      - "7233:7233"   # Temporal server
    environment:
      - DB=postgresql
      - DB_PORT=5432
      - POSTGRES_SEEDS=temporal-db
      - POSTGRES_USER=temporal
      - POSTGRES_PWD=temporal_password
    depends_on:
      temporal-db:
        condition: service_healthy

  temporal-db:
    image: postgres:16-alpine
    container_name: temporal-db
    restart: unless-stopped
    environment:
      POSTGRES_USER: temporal
      POSTGRES_PASSWORD: temporal_password
      POSTGRES_DB: temporal
    volumes:
      - temporal-db-data:/var/lib/postgresql/data
    healthcheck:
      test: ["CMD-SHELL", "pg_isready -U temporal"]
      interval: 10s
      timeout: 5s
      retries: 5

  temporal-ui:
    image: temporalio/ui:latest
    container_name: temporal-ui
    restart: unless-stopped
    ports:
      - "8080:8080"
    environment:
      - TEMPORAL_ADDRESS=temporal:7233

volumes:
  temporal-db-data:

Saga Pattern Implementation

Write a saga as normal code — Temporal handles the durability:

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func OrderSaga(ctx workflow.Context, order OrderRequest) error {
    // Define compensation functions
    activities := &OrderActivities{}

    // Step 1: Reserve inventory
    err := workflow.ExecuteActivity(ctx, activities.ReserveInventory, order).Get(ctx, nil)
    if err != nil {
        return err
    }
    // Compensate: release inventory
    defer func() {
        if workflow.GetLastError(ctx) != nil {
            workflow.ExecuteActivity(ctx, activities.ReleaseInventory, order)
        }
    }()

    // Step 2: Process payment
    err = workflow.ExecuteActivity(ctx, activities.ProcessPayment, order).Get(ctx, nil)
    if err != nil {
        return err
    }
    // Compensate: refund payment
    defer func() {
        if workflow.GetLastError(ctx) != nil {
            workflow.ExecuteActivity(ctx, activities.RefundPayment, order)
        }
    }()

    // Step 3: Create shipping order
    err = workflow.ExecuteActivity(ctx, activities.CreateShipping, order).Get(ctx, nil)
    if err != nil {
        return err
    }

    // Step 4: Send confirmation email
    workflow.ExecuteActivity(ctx, activities.SendConfirmation, order)

    return nil
}

Temporal’s durable execution model means that if any activity fails, the workflow pauses and retries according to your policy. If the saga fails permanently, deferred compensation functions execute automatically.

When to Choose Temporal

• Code-first approach — you want to write workflows as code, not model them visually
• Multi-language teams — SDKs for Go, Java, Python, TypeScript, and .NET
• Modern architecture — started in 2020, designed for cloud-native systems
• Strong community — backed by Temporal Technologies (founded by Cadence creators)

Temporal is open-source under the MIT license. The company offers a managed cloud service, but the self-hosted version is fully functional.

Camunda: BPMN 2.0 Standard with Saga Support

Camunda is a mature process orchestration platform that implements the BPMN 2.0 standard. While primarily known as a workflow engine, Camunda’s transactional outbox pattern and compensation events make it a powerful saga orchestrator.

Key features:

• BPMN 2.0 visual modeling — design sagas in a drag-and-drop editor
• Compensation events for automatic rollback of failed transactions
• Transactional outbox pattern for reliable cross-service communication
• External task pattern for language-agnostic service workers
• Zeebe engine for high-throughput distributed process execution
• REST and gRPC APIs
• Web Modeler for collaborative process design

Docker Compose Configuration

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services:
  camunda:
    image: camunda/camunda:latest
    container_name: camunda
    restart: unless-stopped
    ports:
      - "8080:8080"   # Web interface
      - "26500:26500" # gRPC gateway
      - "9600:9600"   # Prometheus metrics
    environment:
      - CAMUNDA_DB_URL=jdbc:postgresql://camunda-db:5432/camunda
      - CAMUNDA_DB_USER=camunda
      - CAMUNDA_DB_PASSWORD=camunda_password
    depends_on:
      camunda-db:
        condition: service_healthy

  camunda-db:
    image: postgres:16-alpine
    container_name: camunda-db
    restart: unless-stopped
    environment:
      POSTGRES_USER: camunda
      POSTGRES_PASSWORD: camunda_password
      POSTGRES_DB: camunda
    volumes:
      - camunda-db-data:/var/lib/postgresql/data
    healthcheck:
      test: ["CMD-SHELL", "pg_isready -U camunda"]
      interval: 10s
      timeout: 5s
      retries: 5

volumes:
  camunda-db-data:

BPMN Saga with Compensation

Model a saga in BPMN using compensation events:

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<!-- Reserve Inventory Task -->
<serviceTask id="reserveInventory" name="Reserve Inventory" />
<boundaryEvent id="compensationBoundary" attachedToRef="reserveInventory">
  <compensateEventDefinition />
</boundaryEvent>

<!-- Compensation Handler -->
<serviceTask id="releaseInventory" name="Release Inventory" isForCompensation="true" />
<association id="compAssoc" sourceRef="compensationBoundary" targetRef="releaseInventory" />

<!-- If payment fails, trigger compensation -->
<serviceTask id="processPayment" name="Process Payment" />
<sequenceFlow id="paymentFail" sourceRef="processPayment" targetRef="compensationTrigger">
  <conditionExpression>${paymentFailed}</conditionExpression>
</sequenceFlow>

Camunda’s visual BPMN editor makes it easy for business analysts and developers to collaborate on saga definitions. The compensation event mechanism automatically triggers rollback handlers when a step fails.

When to Choose Camunda

• Visual process design — BPMN 2.0 editor for non-technical stakeholders
• Enterprise environments — mature platform with long track record
• Regulated industries — BPMN provides standardized, auditable process models
• Existing Java ecosystem — deep Spring Boot integration

Camunda is available under the Apache 2.0 license for the core engine. The web modeler and enterprise features require a commercial license.

Cadence: The Original Durable Execution Platform

Cadence is the predecessor to Temporal, originally developed at Uber to handle millions of workflow executions. It shares the same code-first approach and durable execution model, making the comparison with Temporal primarily about ecosystem maturity and feature differences.

Key features:

• Code-first workflow definition (Java, Go)
• Durable execution with automatic retry and state persistence
• Activity scheduling with timeout and retry policies
• Signal-based external communication with running workflows
• Domain-based multi-tenancy
• High-throughput execution engine

Docker Compose Configuration

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services:
  cadence:
    image: ubercadence/server:master-auto-setup
    container_name: cadence
    restart: unless-stopped
    ports:
      - "7933:7933"   # Frontend
      - "7934:7934"   # Matching
    environment:
      - DYNAMIC_CONFIG_FILE_PATH=config/dynamicconfig/development_es.yaml
      - CASSANDRA_SEEDS=cassandra
      - KEYSTORE=skip
    depends_on:
      cassandra:
        condition: service_healthy

  cassandra:
    image: cassandra:4.1
    container_name: cadence-cassandra
    restart: unless-stopped
    environment:
      - MAX_HEAP_SIZE=512M
      - HEAP_NEWSIZE=256M
    volumes:
      - cadence-cassandra-data:/var/lib/cassandra
    healthcheck:
      test: ["CMD", "cqlsh", "-e", "describe keyspaces"]
      interval: 30s
      timeout: 10s
      retries: 5

  cadence-web:
    image: ubercadence/web:latest
    container_name: cadence-web
    restart: unless-stopped
    ports:
      - "8088:8088"
    environment:
      - CADENCE_TLIST=127.0.0.1:7933

volumes:
  cadence-cassandra-data:

Note: Cadence uses Cassandra as its default persistence layer, which requires more resources than Temporal’s PostgreSQL option. Community PostgreSQL support exists but may require additional configuration.

When to Choose Cadence

• Existing Uber ecosystem — if your organization already uses Cadence
• Cassandra infrastructure — you have Cassandra expertise and want to leverage it
• Legacy systems — migrating from an existing Cadence deployment
• Research and learning — understanding the foundations of durable execution

Cadence is open-source under the Apache 2.0 license. However, active development has largely shifted to Temporal, so new features and community activity favor the Temporal ecosystem.

Feature Comparison Matrix

Deployment Comparison

Decision Framework

Choose Temporal if:

• You want the most active open-source community for durable execution
• Your team prefers code-first workflow definitions
• You need SDK support for Python, TypeScript, or .NET
• You want PostgreSQL-based persistence (simpler operations than Cassandra)

Choose Camunda if:

• Your business stakeholders need to design and review process flows visually
• BPMN 2.0 compliance is a requirement (government, finance, healthcare)
• You need mature enterprise support and consulting options
• Your team is primarily Java-based with Spring Boot experience

Choose Cadence if:

• You have an existing Cadence deployment to maintain
• Your organization has deep Cassandra expertise
• You’re studying the foundations of durable execution platforms
• You need Uber-proven patterns for extreme-scale workflow processing

Production Deployment Checklist

1. Compensation idempotency — ensure compensation actions can run multiple times safely
2. Workflow timeouts — set appropriate timeouts to prevent stuck sagas
3. Activity heartbeats — enable heartbeats for long-running activities
4. Dead letter queues — capture failed compensations for manual review
5. Monitoring — track workflow completion rates, latency, and error rates
6. Testing — use time-skipping to test saga behavior without real delays
7. Versioning — version workflow definitions to support rolling deployments
8. Capacity planning — size your persistence layer for expected workflow volume

Frequently Asked Questions

What is the saga pattern in microservices?

The saga pattern replaces distributed ACID transactions with a sequence of local transactions. Each step has a corresponding compensation action that undoes it. If any step fails, previously completed steps are compensated in reverse order, ensuring eventual consistency across services.

When should I use a saga orchestrator vs choreography?

Saga orchestration uses a central coordinator (like Temporal or Camunda) to manage the sequence. Choreography relies on events — each service reacts to the previous service’s output. Choose orchestration when you need centralized visibility, retry logic, and compensation management. Choose choreography for simpler workflows with fewer services.

How does Temporal guarantee durable execution?

Temporal persists every workflow state change to its database before acknowledging completion. If a worker crashes mid-execution, another worker picks up the workflow from the last persisted state. Activities that support heartbeats can resume from their last checkpoint, not from the beginning.

Can Camunda handle saga compensation automatically?

Camunda supports BPMN compensation events that trigger rollback handlers when a process instance encounters an error. However, unlike Temporal’s code-first defer pattern, Camunda requires explicit modeling of compensation paths in the BPMN diagram. This gives more visual control but requires more upfront design.

Is Cadence still being actively developed?

Active development has largely shifted to Temporal, which was created by the same team that built Cadence at Uber. Cadence receives maintenance updates but most new features, SDK improvements, and community activity focus on Temporal. For new projects, Temporal is generally recommended over Cadence.

How do saga orchestrators handle partial failures?

When a step fails, the orchestrator examines which previous steps completed successfully and executes their compensation actions in reverse order. For example: if “charge payment” fails after “reserve inventory” succeeded, the orchestrator first calls “release inventory” compensation. The orchestrator tracks all state in its persistence layer, so this works even if the orchestrator itself restarts.

What’s the difference between saga orchestration and workflow orchestration?

Saga orchestration is a specific pattern within workflow orchestration focused on transaction compensation. A saga orchestrator tracks which steps succeeded and can roll them back. A general workflow orchestrator (like Camunda or Temporal) supports sagas but also handles many other patterns: parallel execution, timers, human tasks, and conditional branching.