# Activepieces vs Dafthunk

Activepieces records 258,553 monthly visits with +1.5% month-over-month growth and Freemium pricing. Dafthunk records 799 monthly visits with -50% growth and Free (open source) pricing.

| Metric | [Activepieces](https://openaitools.app/tool/activepieces) | [Dafthunk](https://openaitools.app/tool/dafthunk) |
| :--- | :--- | :--- |
| Website URL | https://www.activepieces.com | https://www.dafthunk.com |
| Categories | AI Workflow, No-Code&Low-Code, AI Code Assistant, AI Agent | AI Workflow, AI Developer Tools, No-Code&Low-Code, AI Agent |
| Pricing Model | Freemium | Free (open source) |
| Monthly Visits | 258,553 | 799 |
| MoM Growth Rate | +1.5% | -50% |
| Primary Market | United States | United States |
| Direct Visits | 111,328 | 237 |
| Review Score | 4.6 | 4.3 |
| Saved Count | 0 | 0 |
| Supported Platforms | Website | Website |

## Activepieces

Activepieces is an AI-first automation platform built around the idea that a team's agents and its people should share one workspace. At the center are AI agents: you describe a job in plain words and the agent works out the steps, the order and which tools to open across your connected apps and any MCP server you point it at. Sensitive steps can be gated behind human approval, so money, customer and production actions stay under control.

Underneath the agent layer sits a mature workflow engine with a visual builder. Chat can draft most of a flow, while branching, retries, waitpoints, subflows, error handling and human approvals handle the hard cases. Where a step needs real logic, you can drop into inline TypeScript and keep the rest visual. Chat, Tables (a lightweight structured data layer), a knowledge base and an MCP server round out the platform so agents and teammates operate on the same data.

The project is open source at its core, with hundreds of contributors maintaining MIT-licensed app pieces, and it deploys flexibly: Activepieces Cloud, your own Docker or Kubernetes infrastructure, or a fully air-gapped install. Enterprise controls include projects and access roles, SSO via Okta or Entra, secret managers such as HashiCorp Vault, audit logs streamed to your SIEM, and bring-your-own AI model keys from Anthropic, OpenAI, AWS Bedrock or Google Gemini.

**Pricing & Plans:** Freemium model: a free plan requiring no credit card lets you start building flows and agents, with paid plans for higher run volumes and enterprise features. Deployment options range from the managed cloud to self-hosted and air-gapped, and open-source users can run the community edition on their own infrastructure.

- **AI agents from plain language:** Describe a task in everyday words and the agent determines the steps, chooses tools from your connected apps and MCP servers, and pauses for approval on sensitive actions.
- **Visual flow builder with inline TypeScript:** Build automations on a canvas with branching, retries, waitpoints, subflows and error handling, then write inline TypeScript for the steps that need real code.
- **770+ open-source app connectors:** Every piece is MIT-licensed and community-built, covering the apps you already run, with an HTTP piece for any REST or GraphQL endpoint with auth and pagination handled.
- **Chat, Tables and knowledge base:** Draft flows by chatting, store structured data in Tables that flows and agents can read and write, and keep internal documents searchable by every agent.
- **Enterprise deployment and governance:** Run on the managed cloud, your Docker/Kubernetes stack or air-gapped, with projects, SSO, role-based access, secret managers, audit logs and bring-your-own AI keys.

**Strengths:** Open-source core with MIT-licensed pieces and a genuinely self-hostable build; Strong blend of AI agents, a visual builder and inline TypeScript; Enterprise-grade controls including SSO, roles, secret managers and audit streaming; Large connector library plus an HTTP piece for anything not covered

**Limitations:** The breadth of agents, tables, flows and MCP features can overwhelm new users; Some advanced enterprise capabilities are reserved for paid and self-managed plans; Self-hosting means you own upgrades, scaling and reliability

[Profile (Markdown)](https://openaitools.app/tool/activepieces.md)

## Dafthunk

:The platform is built on Cloudflare Workers, Workflows, Durable Objects, D1, R2, KV and the Workers Analytics Engine, which is what lets executions scale to zero when idle and back up under load without any infrastructure for you to provision. Durability and automatic retries are part of the runtime, so long sequences of steps survive restarts and transient failures.

AI sits at the centre of the node library: you can wire Anthropic Claude, OpenAI GPT, Google Gemini and Cloudflare Workers AI into text generation, summarisation, translation, sentiment analysis and vision steps, and hand results off to browser automation, media generation or third-party services. The project reports more than 470 nodes, 30+ AI models and a dozen integrations including GitHub, Discord, LinkedIn, Reddit, Google Calendar and Gmail. Because the whole stack is MIT licensed and developed in public on GitHub, you can fork it, self-host it or embed it in a commercial product without paying for the platform itself — you only cover the Cloudflare resources your workflows actually consume.

**Pricing & Plans:** Dafthunk is open source under the MIT license and free to use as a platform — there is no subscription for the workflow engine itself. Cloudflare charges for the underlying serverless resources your workflows consume (Workers, Workflows, D1, R2, Browser Rendering, Queues).

- **Visual drag-and-drop workflow editor:** Design automation pipelines on a drag-and-drop React Flow canvas instead of writing glue code, with live preview and versioning built in.
- **Serverless, durable execution:** Run workflows on Cloudflare Workers and Workflows with durable execution, auto-retry and scale-to-zero behaviour, so long-running jobs survive restarts.
- **Persistent storage and analytics:** Store workflow state and execution history in Cloudflare D1 SQL, R2 object storage, KV and the Workers Analytics Engine for persistent, queryable runs.
- **Flexible triggers and queues:** Start workflows from HTTP webhooks, Cloudflare Queues, cron schedules, email or a manual trigger to cover event-driven, queued and time-based automation.
- **Broad node and integration library:** Tap 470+ nodes across AI models, headless browser scraping and screenshots, image and audio generation, PDF creation and services such as GitHub, Gmail and Google Calendar.

**Strengths:** Fully MIT licensed with no enterprise tier or feature gating; Scales to zero when idle and up with demand on Cloudflare's serverless platform; Durable execution with automatic retries for long-running workflows; Large library of AI, browser, media and integration nodes behind one visual editor

**Limitations:** Requires comfort with technical concepts such as HTTP webhooks, queues and API credentials; Because it is a young open-source project, the node library and documentation are still growing; Not a fully managed turnkey product — you are responsible for your own deployment and maintenance; No official premium support tier or SLA as part of the MIT release

[Profile (Markdown)](https://openaitools.app/tool/dafthunk.md)

## Frequently Asked Questions

### How do Activepieces and Dafthunk compare in monthly traffic?

Activepieces has 258,553 monthly visits, while Dafthunk has 799. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Activepieces has a month-over-month growth rate of +1.5%; Dafthunk has -50%.

### How does pricing compare?

Activepieces: Freemium. Freemium model: a free plan requiring no credit card lets you start building flows and agents, with paid plans for higher run volumes and enterprise features. Deployment options range from the managed cloud to self-hosted and air-gapped, and open-source users can run the community edition on their own infrastructure. Dafthunk: Free (open source). Dafthunk is open source under the MIT license and free to use as a platform — there is no subscription for the workflow engine itself. Cloudflare charges for the underlying serverless resources your workflows consume (Workers, Workflows, D1, R2, Browser Rendering, Queues).

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Zapier](https://openaitools.app/tool/zapier-com) | 5,065,248 | +0.4% | Freemium, Free Trial, Paid | Automate work across thousands of apps — no code required | [.md](https://openaitools.app/tool/zapier-com.md) |
| 2 | [n8n](https://openaitools.app/tool/n8n) | 4,522,449 | -7.4% | Freemium | Open-source workflow automation built for AI agents and technical teams | [.md](https://openaitools.app/tool/n8n.md) |
| 3 | [Apify](https://openaitools.app/tool/apify) | 4,147,762 | +3.9% | Freemium, Contact for Pricing | Run thousands of ready-made web scrapers and AI agents from one cloud platform | [.md](https://openaitools.app/tool/apify.md) |
| 4 | [MindStudio](https://openaitools.app/tool/mindstudio) | 1,793,337 | +14.2% | Contact for Pricing | No-code builder for custom AI agents and workflows | [.md](https://openaitools.app/tool/mindstudio.md) |
| 5 | [Dify](https://openaitools.app/tool/dify-ai) | 819,691 | -15% | Freemium | Build, deploy, and govern production-ready agentic AI workflows | [.md](https://openaitools.app/tool/dify-ai.md) |
| 6 | [Eigent AI](https://openaitools.app/tool/eigent-ai) | 575,703 | +1.4% | Freemium, Free Trial, Contact for Pricing | Open-source desktop AI workforce that runs browser, file, and app tasks for you | [.md](https://openaitools.app/tool/eigent-ai.md) |
| 7 | [Gumloop](https://openaitools.app/tool/gumloop) | 379,557 | -21.1% | Freemium, Paid, Contact for Pricing | Build, share, and control AI agents that actually do the work | [.md](https://openaitools.app/tool/gumloop.md) |
| 8 | [Tines](https://openaitools.app/tool/tines) | 273,260 | +24.4% | Freemium, Contact for Pricing | A secure environment where teams build, deploy and govern AI agents, apps and automations | [.md](https://openaitools.app/tool/tines.md) |
| 9 | [Relevance AI](https://openaitools.app/tool/relevance-ai) | 192,083 | -15.5% | Free Trial, Contact for Pricing | Advanced multi-agent workforce builder for complex tasks, but less suited for traditional webhook integrations. | [.md](https://openaitools.app/tool/relevance-ai.md) |
| 10 | [FlowHunt](https://openaitools.app/tool/flowhunt-io) | 186,190 | 0% | Free Trial, Paid | Specializes in building conversational chatbots and agentic pipelines visually, but lacks broad traditional connector depth. | [.md](https://openaitools.app/tool/flowhunt-io.md) |

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Source: https://openaitools.app/compare/activepieces-vs-dafthunk

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