AgentQLは、LLMやAIエージェントをウェブに接続するための開発者向けツールセットです。AIを活用したクエリ言語を用いて、構造化データを堅牢に抽出し、ウェブ操作を自動化します。脆弱なXPathやCSSセレクタに代わる、強力で自己修復可能な代替手段です。
Apifyは、開発者が「Actor」と呼ばれるデータ抽出ツールを構築、デプロイ、公開できるフルスタックのウェブスクレイピングおよび自動化プラットフォームです。Googleマップ、Instagram、TikTokなどの人気ウェブサイト向けの豊富な構築済みスクレイパーマーケットプレイスを提供し、カスタムソリューションを作成するための堅牢なクラウドインフラを備えています。Python、JavaScript、オープンソースライブラリ、シームレスな統合をサポートし、あらゆる規模のウェブデータ収集を簡素化します。
製品概要
AgentQL 製品概要
AgentQLは、LLMやAIエージェントをウェブに接続するための開発者向けツールセットです。AIを活用したクエリ言語を用いて、構造化データを堅牢に抽出し、ウェブ操作を自動化します。脆弱なXPathやCSSセレクタに代わる、強力で自己修復可能な代替手段です。
Apify 製品概要
Apifyは、開発者が「Actor」と呼ばれるデータ抽出ツールを構築、デプロイ、公開できるフルスタックのウェブスクレイピングおよび自動化プラットフォームです。Googleマップ、Instagram、TikTokなどの人気ウェブサイト向けの豊富な構築済みスクレイパーマーケットプレイスを提供し、カスタムソリューションを作成するための堅牢なクラウドインフラを備えています。Python、JavaScript、オープンソースライブラリ、シームレスな統合をサポートし、あらゆる規模のウェブデータ収集を簡素化します。
Detailed feature comparison
AgentQL vs Apify monthly traffic
Compare AgentQL and Apify by monthly reach, traffic trend, visit depth, top regions, and acquisition sources.
How to interpret the traffic data
In the AgentQL vs Apify monthly traffic comparison, AgentQL currently shows 19.7K visits and Apify shows 4.4M; Apify has about 223.8 times the visible traffic of AgentQL, an absolute difference of about 4.4M visits. This reflects visible reach, not feature quality or paid users.
Both tools provide verified traffic details, so monthly trends, visit depth, regions, and acquisition sources can be compared on the same basis.
AgentQL monthly traffic:
Latest traffic
Monthly traffic trend
- 2025/9: 31K 月間訪問数
- 2026/1: 23.6K 月間訪問数
- 2026/2: 19.9K 月間訪問数
- 2026/3: 24K 月間訪問数
- 2026/4: 19.3K 月間訪問数
- 2026/5: 19.7K 月間訪問数
主要地域
Top 5 countries/regions
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇺🇸United States | 49.81% | 9.8K |
| 🇮🇳India | 20.61% | 4.1K |
| 🇬🇧United Kingdom | 17.65% | 3.5K |
| 🇩🇪Germany | 6.43% | 1.3K |
| 🇻🇳Vietnam | 5.5% | 1.1K |
流入元
| Source type | Percentage | Traffic |
|---|---|---|
| ダイレクト | 81.96% | 16.2K |
| 参照元 | 18.04% | 3.6K |
検索キーワード
Apify monthly traffic:
Latest traffic
Monthly traffic trend
- 2025/9: 1.9M 月間訪問数
- 2026/1: 2.5M 月間訪問数
- 2026/2: 2.5M 月間訪問数
- 2026/3: 3.8M 月間訪問数
- 2026/4: 4.1M 月間訪問数
- 2026/5: 4.4M 月間訪問数
主要地域
Top 5 countries/regions
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇺🇸United States | 40.31% | 1.8M |
| 🇮🇳India | 31.99% | 1.4M |
| 🇧🇷Brazil | 10.35% | 457.4K |
| 🇬🇧United Kingdom | 8.77% | 387.5K |
| 🇩🇪Germany | 8.58% | 379.1K |
流入元
| Source type | Percentage | Traffic |
|---|---|---|
| ダイレクト | 84.73% | 3.7M |
| 参照元 | 11.9% | 525.9K |
| Eメール | 3.37% | 148.9K |
検索キーワード
Usage comparison
Compare the core capabilities of AgentQL and Apify
AgentQL Core features
Apify Core features
Use cases
AgentQL Use cases
Apify Use cases
AgentQL vs Apify:In-depth comparison and selection guidance
First decide whether the products solve the same kind of need
This in-depth AgentQL vs Apify comparison uses only the product records, taxonomy, audience, traffic, and community signals available on this page. AgentQL is primarily listed under “LLM”, while Apify is primarily listed under “データ収集”, so the first decision is whether your actual task matches their recorded scope.
The structured fields currently show these decision-relevant differences: Primary category (AgentQL: LLM; Apify: データ収集); Monthly visits (AgentQL: 19.7K; Apify: 4.4M); Monthly growth (AgentQL: 2.3%; Apify: 7%); Website (AgentQL: www.agentql.com; Apify: apify.com); Added (AgentQL: 2025-08-02; Apify: 2025-08-16). These facts are more useful for selection than brand visibility alone.
What market visibility and monthly traffic mean
In the AgentQL vs Apify monthly traffic comparison, AgentQL currently shows 19.7K visits and Apify shows 4.4M; Apify has about 223.8 times the visible traffic of AgentQL, an absolute difference of about 4.4M visits. This reflects visible reach, not feature quality or paid users.
Both tools provide verified traffic details, so monthly trends, visit depth, regions, and acquisition sources can be compared on the same basis.
If public market visibility is an important first-pass criterion, investigate Apify first. The final choice should still follow taxonomy, use case, and a real trial because higher traffic does not prove broader capabilities or better workflow fit.
Product positioning, use cases, and roles
AgentQL and Apify currently overlap in shared categories: データ抽出、ウェブスクレイピング、自動化; shared tags: API、自動化、データ抽出、Webスクレイピング. This can place both on the same shortlist, but it does not prove equal implementation, depth, or cost.
AgentQL's unique categories/tags are LLM、AIエージェント、開発者ツール、ラングチェーン、大規模言語モデル、PDF解析、プレイライト、構造化データ; Apify's are データ収集、AIデータ、データマイニング、開発者ツール、JavaScript、リード生成、Python、検索拡張生成. These unique fields are the strongest differentiators: validate the product whose recorded scope matches the task instead of following traffic alone.
What ratings, comments, and favorites can tell you
AgentQL has no verified rating, 0 comments, 102 favorites, and 118 likes;Apify has no verified rating, 0 comments, 102 favorites, and 104 likes。
Neither product has enough rating or comment samples for a credible reputation ranking.
Selection guidance by actual need
When to evaluate AgentQL first
Put AgentQL on the priority trial list when the task aligns with “LLM” and especially LLM、AIエージェント、開発者ツール、ラングチェーン、大規模言語モデル、PDF解析. This follows recorded positioning and does not imply unlisted capabilities are absent.
AgentQL also currently records: pricing is freemium, product type is website, 19.7K verified monthly visits, no verified user rating. Verify any hard requirement around price, platform, or reach before trial, and do not let sparse review data substitute for testing.
When to evaluate Apify first
Put Apify on the priority trial list when the task aligns with “データ収集” and especially データ収集、AIデータ、データマイニング、開発者ツール、JavaScript、リード生成. This follows recorded positioning and does not imply unlisted capabilities are absent.
Apify also currently records: pricing is freemium, product type is website, 4.4M verified monthly visits, no verified user rating. Verify any hard requirement around price, platform, or reach before trial, and do not let sparse review data substitute for testing.
How to validate the recommendation before deciding
The available data describes positioning, public visibility, and community signals, but it cannot prove output quality, speed, integration effort, privacy, or long-term cost in your workflow. Before deciding, run the same representative tasks in AgentQL and Apify, then record completion time, accuracy, manual corrections, and the real paid threshold. A like-for-like trial turns this comparison into a defensible adoption decision.
比較 FAQ
How should I choose between AgentQL and Apify?
Where does this comparison data come from?
What do unknown fields mean?
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