Baseは、学者や学習者のためのAI搭載研究プラットフォームです。2億4000万件以上の論文を検索し、インタラクティブなグラフで研究のランドスケープを可視化し、研究成果を整理し、AIチャットを使って信頼できる情報源からより深い洞察を引き出すことができます。
Rayyanは、研究者がシステマティックレビューや文献レビューを加速させるために設計されたAI搭載プラットフォームです。自動スクリーニング、重複検出、リアルタイムコラボレーションなどの機能でプロセスを合理化し、研究者のスクリーニング時間を最大90%削減します。80万人以上のユーザーに信頼されており、データインポートから最終報告までのレビューライフサイクル全体をサポートします。
製品概要
Base 製品概要
Baseは、学者や学習者のためのAI搭載研究プラットフォームです。2億4000万件以上の論文を検索し、インタラクティブなグラフで研究のランドスケープを可視化し、研究成果を整理し、AIチャットを使って信頼できる情報源からより深い洞察を引き出すことができます。
Rayyan 製品概要
Rayyanは、研究者がシステマティックレビューや文献レビューを加速させるために設計されたAI搭載プラットフォームです。自動スクリーニング、重複検出、リアルタイムコラボレーションなどの機能でプロセスを合理化し、研究者のスクリーニング時間を最大90%削減します。80万人以上のユーザーに信頼されており、データインポートから最終報告までのレビューライフサイクル全体をサポートします。
Detailed feature comparison
Base vs Rayyan monthly traffic
Compare Base and Rayyan by monthly reach, traffic trend, visit depth, top regions, and acquisition sources.
How to interpret the traffic data
In the Base vs Rayyan monthly traffic comparison, Base currently shows 6.2K visits and Rayyan shows 1.1M; Rayyan has about 174.2 times the visible traffic of Base, an absolute difference of about 1.1M 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.
Base monthly traffic:
Latest traffic
Monthly traffic trend
- 2026/1: 16.3K 月間訪問数
- 2026/2: 5.5K 月間訪問数
- 2026/3: 3.6K 月間訪問数
- 2026/4: 1.8K 月間訪問数
- 2026/5: 6.2K 月間訪問数
主要地域
Top 5 countries/regions
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇮🇳India | 98.83% | 6.2K |
| 🇺🇸United States | 1.17% | 73 |
流入元
| Source type | Percentage | Traffic |
|---|---|---|
| ダイレクト | 86.88% | 5.4K |
| 参照元 | 13.12% | 820 |
検索キーワード
Rayyan monthly traffic:
Latest traffic
Monthly traffic trend
- 2025/9: 917.4K 月間訪問数
- 2026/1: 942.9K 月間訪問数
- 2026/2: 1M 月間訪問数
- 2026/3: 1.1M 月間訪問数
- 2026/4: 1.1M 月間訪問数
- 2026/5: 1.1M 月間訪問数
主要地域
Top 5 countries/regions
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇺🇸United States | 32.99% | 359.1K |
| 🇧🇷Brazil | 31.2% | 339.6K |
| 🇬🇧United Kingdom | 20.31% | 221K |
| 🇵🇰Pakistan | 7.75% | 84.3K |
| 🇵🇹Portugal | 7.75% | 84.3K |
流入元
| Source type | Percentage | Traffic |
|---|---|---|
| ダイレクト | 80.86% | 880.1K |
| 参照元 | 14.66% | 159.6K |
| Eメール | 4.48% | 48.8K |
検索キーワード
Usage comparison
Compare the core capabilities of Base and Rayyan
Base Core features
Rayyan Core features
Use cases
Base Use cases
Rayyan Use cases
Best suited roles
Base Best suited roles
Rayyan Best suited roles
Base vs Rayyan:In-depth comparison and selection guidance
First decide whether the products solve the same kind of need
This in-depth Base vs Rayyan comparison uses only the product records, taxonomy, audience, traffic, and community signals available on this page. Base is primarily listed under “学術”, while Rayyan is primarily listed under “学術”, so the first decision is whether your actual task matches their recorded scope.
The structured fields currently show these decision-relevant differences: Monthly visits (Base: 6.2K; Rayyan: 1.1M); Monthly growth (Base: 255.1%; Rayyan: -4%); Favorites (Base: 102; Rayyan: 128); Website (Base: basedid.com; Rayyan: rayyan.ai); Added (Base: 2025-11-08; Rayyan: 2025-09-11). These facts are more useful for selection than brand visibility alone.
What market visibility and monthly traffic mean
In the Base vs Rayyan monthly traffic comparison, Base currently shows 6.2K visits and Rayyan shows 1.1M; Rayyan has about 174.2 times the visible traffic of Base, an absolute difference of about 1.1M 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 Rayyan 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
Base and Rayyan currently overlap in shared categories: 学術、研究; shared tags: 文献レビュー、研究; shared roles: データアナリスト、司書、政策アナリスト、科学者. This can place both on the same shortlist, but it does not prove equal implementation, depth, or cost.
Base's unique categories/tags are 文献レビュー、学術論文、AI検索、引用分析、データ視覚化、知識管理、OpenAlex、研究アシスタント; Rayyan's are 学術、AIスクリーニング、コラボレーション、データ分析、重複排除、医学研究、Prisma、科学執筆. 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
Base has no verified rating, 0 comments, 102 favorites, and 106 likes;Rayyan has no verified rating, 0 comments, 128 favorites, and 116 likes。
Neither product has enough rating or comment samples for a credible reputation ranking.
Selection guidance by actual need
When to evaluate Base first
Put Base on the priority trial list when the task aligns with “学術” and especially 文献レビュー、学術論文、AI検索、引用分析、データ視覚化、知識管理, or the users include 学術研究者、ジャーナリスト、研究開発プロフェッショナル、学生. This follows recorded positioning and does not imply unlisted capabilities are absent.
Base also currently records: pricing is freemium, product type is website, 6.2K 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 Rayyan first
Put Rayyan on the priority trial list when the task aligns with “学術” and especially 学術、AIスクリーニング、コラボレーション、データ分析、重複排除、医学研究, or the users include 学術的、医療従事者、博士課程学生、公衆衛生専門家. This follows recorded positioning and does not imply unlisted capabilities are absent.
Rayyan also currently records: pricing is freemium, product type is website, 1.1M 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 Base and Rayyan, 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.




