#1載入中…
正面對決基準比較
Apify vs Pig
Apify 每月有 4,147,762 次造訪，月增率 +3.9%，定價模式為免費增值、需聯絡報價。Pig 每月有 1,521 次造訪，成長率 -52.9%，定價模式為需聯絡報價。
Apify 每月有 4,147,762 次造訪，月增率 +3.9%，定價模式為免費增值、需聯絡報價。Pig 每月有 1,521 次造訪，成長率 -52.9%，定價模式為需聯絡報價。
| 主要市場與市佔 | 🇺🇸 美國 (22.2%) | 🇺🇸 美國 (100%) |
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| 每月直接造訪 | 181.64萬 | 597 |
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| 使用者評分 | 4.6 | 4.2 |
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| 支援平台 | 網站 | 網站 |
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一站式雲端平台，執行大量現成網頁擷取工具與 AI 代理
超過十萬個現成擷取器與自動化工具，涵蓋社群媒體、地圖商家、電商、房地產與通用網頁爬取。
把 Apify Actor 直接接進 AI 助手與代理，讓它們能搜尋商店、執行爬蟲，並以工具呼叫取得結構化結果。
平台內建代管代理輪換與反封鎖能力，目標網站加強防護時擷取仍能穩定運作。
開源爬蟲函式庫加上 Python、JavaScript SDK，可用 Playwright、Puppeteer、Selenium 或 Cheerio 打造自訂 Actor。
Pig is an API and SDK that lets developers automate Windows applications with a computer-use AI, through a chat interface, a task API, or a low-level SDK with human-in-the-loop control.
Pig Chat connects your machines and lets you prototype automations through a conversational interface, no code required.
The Agent API exposes the same computer-use AI behind Pig Chat so you can launch tasks from your own services.
A low-level SDK provides the base toolkit for building custom agents, using natural tools like click(), type(), and screenshot().
Agents control the screen the way a person would, transferring control to a human operator for critical steps and picking it back up afterwards.
#1免費 / 開源透過 API 提供直接對應 LLM 的 Markdown 轉換，但缺乏 Apify 豐富的現成爬蟲市集。
專項更強Automates complex business workflows with AI agents, but is less specialized for raw large-scale web scraping actors.
免費 / 開源Mastra is an open-source TypeScript framework for building, deploying, and observing AI agents and workflows. It gives JavaScript developers typed agents, durable workflows, memory, MCP tool support, and built-in observability so prototypes can scale into production.
一組相容 OpenAI 的 API，串接 500+ 圖像、影片、音訊與大模型
免費 / 開源透過 API 打造、測試並部署正式環境的語音 AI 代理
專項更強Automates complex business workflows with AI agents, but is less specialized for raw large-scale web scraping actors.
免費 / 開源Mastra is an open-source TypeScript framework for building, deploying, and observing AI agents and workflows. It gives JavaScript developers typed agents, durable workflows, memory, MCP tool support, and built-in observability so prototypes can scale into production.
