How Camunda 8 Stores Workflow State (Zeebe Internals Explained)
Zeebe Architecture Overview
✍️ Introduction
If you’re coming from Camunda 7 (DB-based engine), understanding how Camunda 8 (Zeebe) stores workflow state is a game changer.
Instead of storing process state in a relational database, Zeebe uses a distributed event-driven architecture — making it:
- ⚡ Highly scalable
- 🔁 Fault tolerant
- 🚀 Extremely fast
👉 Let’s break this down in a simple, practical way.
🧩 1. Core Idea: Event-Sourced State
In Zeebe:
❌ No central database
✅ Workflow state = event stream (log of events)
Every action in a workflow becomes an event:
- Process started
- Task activated
- Variable updated
- Task completed
These events are written sequentially to a log.
📌 This is similar to Kafka-style architecture.
👉 Zeebe stores state as event streams on disk across brokers
🖼️ Event Stream Concept
⚙️ 2. How State is Actually Stored
Let’s simplify:
🧱 Step-by-step
- Client sends command
→ via Gateway (REST/gRPC) - Gateway routes to a Broker
Broker writes an event:
PROCESS_INSTANCE_CREATED
TASK_ACTIVATED
VARIABLE_UPDATED- Event is:
- Stored in log (append-only)
- Replicated to other brokers
- Internal state is rebuilt from events
🧠 Important Concept
👉 State = Result of replaying events
Not stored directly like:
status = COMPLETED
Instead:
EVENT 1 → started
EVENT 2 → task1 completed
EVENT 3 → task2 completed
🧩 3. Role of Brokers & Partitions
🖼️ Brokers & Partitions
Zeebe is distributed by design:
- Multiple brokers
- Each broker holds partitions
- Each partition has:
- Leader
- Followers (replication)
👉 This ensures:
- No data loss
- High availability
- Horizontal scaling
📌 Data is replicated across brokers, eliminating single point of failure
🔄 4. State Reconstruction (Replay Mechanism)
If a broker crashes:
- It restarts
- Reads event log
- Rebuilds workflow state
👉 This is called state replay
📌 That’s why:
- No DB recovery needed
- No complex transactions
- Faster recovery
⚡ 5. Why This is Better than Camunda 7
| Feature | Camunda 7 | Camunda 8 (Zeebe) |
|---|---|---|
| Storage | RDBMS | Event log |
| Scaling | Vertical | Horizontal |
| State | Stored in tables | Reconstructed |
| Bottleneck | DB | Distributed |
| Performance | Moderate | High throughput |
📌 Zeebe avoids DB bottlenecks by using distributed logs
🧠 6. Internal Components That Handle State
🔹 Gateway
- Entry point
- Routes requests
🔹 Broker
- Stores event log
- Executes workflow logic
🔹 Exporters
- Push data to:
- Elasticsearch
- Monitoring tools
🔹 Clients
- Interact via API
- Execute business logic
📌 Zeebe separates orchestration from business logic
🖼️ End-to-End Flow
🚀 7. Real-Life Example
Order Processing Workflow
- Order Created → Event
- Payment Task → Event
- Payment Completed → Event
- Shipping Triggered → Event
👉 Entire workflow = sequence of events
💡 Key Takeaways
- ✅ Zeebe stores workflow state as event streams
- ✅ No traditional database dependency
- ✅ State is rebuilt, not stored
- ✅ Distributed architecture = scalability
- ✅ Perfect for microservices orchestration
📚 Recommended Articles
👉 Camunda + Database Design (History tables, optimization, scaling)
👉 Securing Workflows in Camunda 8 (Auth & Roles)
👉 Java + Spring Security (Authentication & Authorization
French Version: https://shikhanirankari.blogspot.com/2026/04/comment-camunda-stocke-letat-des.html
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