Datafold
分析 · 21K 月間訪問数
Datafoldは、データエンジニアリングチーム向けのAI搭載プラットフォームで、データ品質テスト、モニタリング、移行を自動化します。データ差分比較（diffing）を使用してデータセットを比較し、CI/CDでの問題の事前検出を可能にし、複雑なデータ移行中に100%のパリティを確保して、タイムラインを最大6倍高速化します。
製品概要
Datafold 製品概要
Datafoldは、データエンジニアリングチーム向けのAI搭載プラットフォームで、データ品質テスト、モニタリング、移行を自動化します。データ差分比較（diffing）を使用してデータセットを比較し、CI/CDでの問題の事前検出を可能にし、複雑なデータ移行中に100%のパリティを確保して、タイムラインを最大6倍高速化します。
Preview
Metaplane 製品概要
Metaplaneは、現代のデータチーム向けのエンドツーエンドのデータオブザーバビリティプラットフォームです。機械学習を利用してデータスタックを自動的に監視し、ビジネスに影響を与える前に潜在的なデータ品質問題を検出し、完全なコンテキスト付きで実用的なアラートを提供します。
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Detailed feature comparison
| Feature | Datafold | Metaplane |
|---|---|---|
| 主要カテゴリー | 分析 | 分析 |
| 追加日 | 2025-08-11 | 2025-08-10 |
| 価格 | 有料 | フリーミアム |
| 公式サイト | www.datafold.com | www.metaplane.dev |
| 製品タイプ | ウェブサイト | ウェブサイト |
| Performance data | ||
| ユーザー評価 | 未確認 | 未確認 |
| コメント | 0 | 0 |
| 月間訪問数 | 21K | 26.5K |
| 月間成長率 | 1% | 3% |
| お気に入り | 105 | 91 |
| Details | 詳細を見る | 詳細を見る |
Datafold vs Metaplane monthly traffic
Compare Datafold and Metaplane by monthly reach, traffic trend, visit depth, top regions, and acquisition sources.
How to interpret the traffic data
In the Datafold vs Metaplane monthly traffic comparison, Datafold currently shows 21K visits and Metaplane shows 26.5K; Metaplane has about 1.3 times the visible traffic of Datafold, an absolute difference of about 5.5K 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.
Datafold monthly traffic:
Latest traffic
月間訪問数
21K
平均滞在時間
1:16
訪問あたりページ数
2.13
直帰率
39.96%
Data updated 2026-06-15
Monthly traffic trend
- 2025/9: 33.5K 月間訪問数
- 2026/1: 24.6K 月間訪問数
- 2026/2: 19.6K 月間訪問数
- 2026/3: 26.3K 月間訪問数
- 2026/4: 20.8K 月間訪問数
- 2026/5: 21K 月間訪問数
主要地域
Top 5 countries/regions
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇺🇸United States | 54.41% | 11.4K |
| 🇻🇳Vietnam | 13.86% | 2.9K |
| 🇮🇳India | 12.19% | 2.6K |
| 🇹🇭Thailand | 10.7% | 2.2K |
| 🇵🇰Pakistan | 8.84% | 1.9K |
流入元
| Source type | Percentage | Traffic |
|---|---|---|
| ダイレクト | 94.33% | 19.8K |
| 参照元 | 5.67% | 1.2K |
検索キーワード
data-diffdatafolddbt pythonnutrafol revenueopen source data warehouse
Metaplane monthly traffic:
Latest traffic
月間訪問数
26.5K
平均滞在時間
2:39
訪問あたりページ数
9.75
直帰率
33.59%
Data updated 2026-06-15
Monthly traffic trend
- 2025/9: 36.9K 月間訪問数
- 2026/1: 33.4K 月間訪問数
- 2026/2: 37.4K 月間訪問数
- 2026/3: 30.9K 月間訪問数
- 2026/4: 25.7K 月間訪問数
- 2026/5: 26.5K 月間訪問数
主要地域
Top 5 countries/regions
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇺🇸United States | 75.27% | 20K |
| 🇻🇳Vietnam | 7.21% | 1.9K |
| 🇮🇳India | 6.88% | 1.8K |
| 🇧🇷Brazil | 5.54% | 1.5K |
| 🇮🇩Indonesia | 5.1% | 1.4K |
流入元
| Source type | Percentage | Traffic |
|---|---|---|
| ダイレクト | 97.17% | 25.8K |
| 参照元 | 2.83% | 750 |
検索キーワード
anomaliesdata anomaly meaningdata validation in marketing researchgoogle big query rows in tablesmetaplane
Traffic-based selection guidance: If public market visibility is an important first-pass criterion, investigate Metaplane 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.
Usage comparison
Compare the core capabilities of Datafold and Metaplane
Datafold Core features
データベース
分析
自動化
Metaplane Core features
データベース
分析
可観測性
モニタリング
Use cases
Datafold Use cases
CI/CD
データエンジニアリング
データ可観測性
データ品質
dbt
自動化
データベース
データ移行
データテスト
データ検証
SQL
Metaplane Use cases
CI/CD
データエンジニアリング
データ可観測性
データ品質
dbt
アナリティクス
異常検知
BigQuery
データガバナンス
データ監視
血統
雪の結晶
Datafold vs Metaplane：In-depth comparison and selection guidance
First decide whether the products solve the same kind of need
This in-depth Datafold vs Metaplane comparison uses only the product records, taxonomy, audience, traffic, and community signals available on this page. Datafold is primarily listed under “分析”, while Metaplane is primarily listed under “分析”, so the first decision is whether your actual task matches their recorded scope.
The structured fields currently show these decision-relevant differences: Primary category (Datafold: 分析; Metaplane: 分析); Pricing (Datafold: Paid; Metaplane: Freemium); Monthly visits (Datafold: 21K; Metaplane: 26.5K); Monthly growth (Datafold: 1%; Metaplane: 3%); Favorites (Datafold: 105; Metaplane: 91). These facts are more useful for selection than brand visibility alone.
What market visibility and monthly traffic mean
In the Datafold vs Metaplane monthly traffic comparison, Datafold currently shows 21K visits and Metaplane shows 26.5K; Metaplane has about 1.3 times the visible traffic of Datafold, an absolute difference of about 5.5K 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 Metaplane 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
Datafold and Metaplane currently overlap in shared categories: データベース; shared tags: CI/CD、データエンジニアリング、データ可観測性、データ品質、dbt. This can place both on the same shortlist, but it does not prove equal implementation, depth, or cost.
Datafold's unique categories/tags are 分析、自動化、データベース、データ移行、データテスト、データ検証、SQL; Metaplane's are 分析、可観測性、モニタリング、アナリティクス、異常検知、BigQuery、データガバナンス、データ監視. 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
Datafold has no verified rating, 0 comments, 105 favorites, and 120 likes；Metaplane has no verified rating, 0 comments, 91 favorites, and 105 likes。
Neither product has enough rating or comment samples for a credible reputation ranking.
Selection guidance by actual need
When to evaluate Datafold first
Put Datafold on the priority trial list when the task aligns with “分析” and especially 分析、自動化、データベース、データ移行、データテスト、データ検証. This follows recorded positioning and does not imply unlisted capabilities are absent.
Datafold also currently records: pricing is paid, product type is website, 21K 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 Metaplane first
Put Metaplane on the priority trial list when the task aligns with “分析” and especially 分析、可観測性、モニタリング、アナリティクス、異常検知、BigQuery. This follows recorded positioning and does not imply unlisted capabilities are absent.
Metaplane also currently records: pricing is freemium, product type is website, 26.5K 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 Datafold and Metaplane, 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 Datafold and Metaplane?
Compare positioning, pricing, taxonomy, and traffic maturity, then verify the latest details on each official website.
Where does this comparison data come from?
The factual baseline is derived from product, taxonomy, traffic, and community data. Reviewed editorial conclusions show their source and verification date.
What do unknown fields mean?
Unknown means there is not enough reliable evidence; the page does not fill gaps with assumptions.