# Activepieces vs Ask On Data

Activepieces records 258,553 monthly visits with +1.5% month-over-month growth and Freemium pricing. Ask On Data records 0 monthly visits with -100% growth and Freemium pricing.

| Metric | [Activepieces](https://openaitools.app/tool/activepieces) | [Ask On Data](https://openaitools.app/tool/ask-on-data) |
| :--- | :--- | :--- |
| Website URL | https://www.activepieces.com | https://askondata.com |
| Categories | AI Workflow, No-Code&Low-Code, AI Code Assistant, AI Agent | AI Agent, AI Chatbot, Large Language Models (LLMs), Open Source AI Models |
| Pricing Model | Freemium | Freemium |
| Monthly Visits | 258,553 | 0 |
| MoM Growth Rate | +1.5% | -100% |
| Primary Market | United States | Global |
| Direct Visits | 111,328 | 0 |
| Review Score | 4.6 | 4.4 |
| 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)

## Ask On Data

Ask On Data targets the part of data engineering that has historically required the most ceremony: getting from a business request to a working pipeline. Instead of wiring transformations by hand, you type what you need in natural language and an agent turns that intent into a structured pipeline, showing a live preview of the data after each instruction. Beyond the chat surface it also accepts SQL, Python and direct YAML edits, so teams are not boxed in when a transformation needs precision.

The platform is built on Python and React, and the pipelines it generates are Apache Spark jobs that can be orchestrated and scheduled. Supporting components include Langchain, Ollama and Airbyte. Jobs can be triggered manually or scheduled to run at a set frequency with full load, incremental load or truncate-and-load semantics, and the full action history gives you an audit trail plus undo for any step.

Ask On Data is offered as an open-source project as well as a managed cloud service, and the managed option removes infrastructure and maintenance work while still allowing deployment on a cloud of your choosing. The vendor positions the tool as a large cost saving compared with traditional data engineering stacks, largely because pipelines are authored in a fraction of the usual time. Documented use cases span data integration such as joins and unions, data cleaning, wrangling, custom calculations and broader transformation work.

**Pricing & Plans:** Self-hosting of the open-source edition is free. The managed/enterprise edition is priced by the volume of data processed, so you need to contact the vendor for a quote. A free trial registration is available from the site.

- **Conversational pipeline building:** Create, manage and optimise data pipelines by describing what you want in plain language, with no code required for standard transformations.
- **Live data preview and undo:** Every instruction returns a real-time preview of the affected data, and any step can be rolled back from the action history before you commit.
- **Escape hatches for complex cases:** Drop into SQL, Python or the underlying YAML when edge cases demand precise control, and add Apache Spark code at schedule time.
- **End-to-end scheduling:** Orchestrate complete pipelines on a defined frequency with full load, incremental load, truncate-and-load and similar strategies.
- **Broad source connectivity:** Connect flat files, APIs, databases, data lakes, data warehouses and log files, with custom data source support available on request.

**Strengths:** Natural-language pipeline authoring dramatically shortens the path from request to working job; Full SQL, Python, YAML and Spark escape hatches keep advanced users in control; Live previews plus undo and action history make AI-generated transformations reviewable; Free self-hosting option lowers the barrier for teams that want to evaluate it properly

**Limitations:** Pricing for the managed edition is quote-only, which complicates budgeting before a conversation; Effective use of the escape hatches assumes familiarity with Spark, SQL and YAML concepts; As an AI-driven tool, generated pipelines should still be reviewed before touching production data

[Profile (Markdown)](https://openaitools.app/tool/ask-on-data.md)

## Frequently Asked Questions

### How do Activepieces and Ask On Data compare in monthly traffic?

Activepieces has 258,553 monthly visits, while Ask On Data has 0. 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%; Ask On Data has -100%.

### 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. Ask On Data: Freemium. Self-hosting of the open-source edition is free. The managed/enterprise edition is priced by the volume of data processed, so you need to contact the vendor for a quote. A free trial registration is available from the site.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [DeepSeek](https://openaitools.app/tool/deepseek) | 372,761,591 | +4.3% | Freemium | High-efficiency open-weight and hosted reasoning AI powered by DeepSeek-V4 and R1 at ultra-low token costs. | [.md](https://openaitools.app/tool/deepseek.md) |
| 2 | [Ollama](https://openaitools.app/tool/ollama) | 9,421,973 | +4.3% | Free, Freemium, Paid | Run and build with open AI models locally or in the cloud | [.md](https://openaitools.app/tool/ollama.md) |
| 3 | [Zapier](https://openaitools.app/tool/zapier-com) | 5,065,248 | +0.4% | Freemium, Free Trial, Paid | Massive prebuilt app ecosystem and polished UX, but significantly more expensive and proprietary. | [.md](https://openaitools.app/tool/zapier-com.md) |
| 4 | [n8n](https://openaitools.app/tool/n8n) | 4,522,449 | -7.4% | Freemium | Powerful open-source workflow automation with robust self-hosting options, but steeper learning curve than Activepieces. | [.md](https://openaitools.app/tool/n8n.md) |
| 5 | [MindStudio](https://openaitools.app/tool/mindstudio) | 1,793,337 | +14.2% | Contact for Pricing | Streamlined interface for deploying custom AI agents, but less flexible for traditional data integration pipelines. | [.md](https://openaitools.app/tool/mindstudio.md) |
| 6 | [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) |
| 7 | [Open WebUI](https://openaitools.app/tool/open-webui) | 804,534 | -2.8% | Freemium | Self-hosted AI workspace for local and cloud models | [.md](https://openaitools.app/tool/open-webui.md) |
| 8 | [LobeHub](https://openaitools.app/tool/lobehub) | 654,548 | -25% | Freemium | Put always-on AI agents on your team chat | [.md](https://openaitools.app/tool/lobehub.md) |
| 9 | [LlamaIndex](https://openaitools.app/tool/llamaindex) | 387,910 | +19.9% | Freemium, Contact for Pricing | Turn any document into AI-ready context with agentic parsing and extraction | [.md](https://openaitools.app/tool/llamaindex.md) |
| 10 | [Gumloop](https://openaitools.app/tool/gumloop) | 379,557 | -21.1% | Freemium, Paid, Contact for Pricing | Excellent browser and web scraping automation features for AI agents, but fewer standard enterprise app integrations. | [.md](https://openaitools.app/tool/gumloop.md) |

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Source: https://openaitools.app/compare/activepieces-vs-ask-on-data

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