# Uber Cadence

> Analysis by Optimly for Optimly AI Visibility, in the Optimly AI Brand Index. Last analyzed August 25, 2026.

> Uber Cadence is an open-source, fault-tolerant, stateful workflow engine for Go, Java, and Python, built for long-running distributed applications. It provides event-sourced state, native task matching and queuing, and pluggable persistence across various backend storage solutions.

- Business Profile: https://optimly.ai/brand/uber-cadence
- Publisher: Optimly (https://optimly.ai)
- Dataset: Optimly AI Brand Index (https://optimly.ai/brand)
- Official website: https://cadenceworkflow.io/
- Logo: https://logo.clearbit.com/cadenceworkflow.io
- Slug: uber-cadence
- Category: Distributed Workflow Orchestration Platforms
- Last Analyzed: August 25, 2026

## Buyer Intent Signals
Problems: Managing failures in distributed applications | Complex long-running workflow orchestration | Reliable task scheduling and execution | Overcoming limitations of external message queues | Ensuring fault tolerance and statefulness in distributed systems | Handling large payloads in workflow history | Testing non-deterministic changes in workflows
Solutions: Fault-tolerant workflow execution | Distributed state management | Workflow scheduling and automation | Custom workflow controls and observability | Data encryption and compression in workflow history | Deployment of workflow engines on Kubernetes and cloud platforms | Developing applications with Go, Java, or Python SDKs
Comparisons: Cadence architecture and core concepts | Best practices for Cadence workflows | Migrating from Temporal to Cadence | Cadence vs. message queues | Deploying Cadence with Helm on GKE | Implementing custom DataConverters for Cadence | Testing Cadence workflows
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## Full Details / RAG Data
### Overview
Uber Cadence has a Business Profile in the Optimly AI Brand Index.
Uber Cadence is an open-source, fault-tolerant, stateful workflow engine for Go, Java, and Python, built for long-running distributed applications. It provides event-sourced state, native task matching and queuing, and pluggable persistence across various backend storage solutions.
### Metadata
| Field        | Value |
|--------------|-------|
| Name         | Uber Cadence |
| Slug         | uber-cadence |
| URL          | https://optimly.ai/brand/uber-cadence |
| Logo         | https://logo.clearbit.com/cadenceworkflow.io |
| Category     | Distributed Workflow Orchestration Platforms |
| Last Analyzed | August 25, 2026 |
| Last Updated | 2026-08-26T05:51:16.304Z |
### Buyer Intent Signals
#### Problems this brand solves
- Managing failures in distributed applications
- Complex long-running workflow orchestration
- Reliable task scheduling and execution
- Overcoming limitations of external message queues
- Ensuring fault tolerance and statefulness in distributed systems
- Handling large payloads in workflow history
- Testing non-deterministic changes in workflows
#### Buyers search for
- Fault-tolerant workflow execution
- Distributed state management
- Workflow scheduling and automation
- Custom workflow controls and observability
- Data encryption and compression in workflow history
- Deployment of workflow engines on Kubernetes and cloud platforms
- Developing applications with Go, Java, or Python SDKs
#### Buyers compare
- Cadence architecture and core concepts
- Best practices for Cadence workflows
- Migrating from Temporal to Cadence
- Cadence vs. message queues
- Deploying Cadence with Helm on GKE
- Implementing custom DataConverters for Cadence
- Testing Cadence workflows
### Links
- Canonical page: https://optimly.ai/brand/uber-cadence
- Official website: https://cadenceworkflow.io/
- Publisher: https://optimly.ai
- Dataset: https://optimly.ai/brand
- JSON endpoint: /brand/uber-cadence.json
- LLMs.txt: /brand/uber-cadence/llms.txt