ClickHouse
データベース · 786.3K 月間訪問数
ClickHouseは、高性能なオープンソースの列指向OLAPデータベース管理システムです。大規模データのリアルタイム分析向けに設計されており、オブザーバビリティ、BI、ML/GenAIなどのための超高速クエリを実現しつつ、リソース効率とコスト効率を両立させています。
VS
SheetQuery
データベース · 643 月間訪問数
Google Sheets上で直接高度なSQLクエリを実行し、洗練されたデータ分析、一括更新、削除、挿入を可能にする強力なツール。スプレッドシートをクエリ可能なデータベースに変換します。
製品概要
ClickHouse 製品概要
ClickHouseは、高性能なオープンソースの列指向OLAPデータベース管理システムです。大規模データのリアルタイム分析向けに設計されており、オブザーバビリティ、BI、ML/GenAIなどのための超高速クエリを実現しつつ、リソース効率とコスト効率を両立させています。
Preview
SheetQuery 製品概要
Google Sheets上で直接高度なSQLクエリを実行し、洗練されたデータ分析、一括更新、削除、挿入を可能にする強力なツール。スプレッドシートをクエリ可能なデータベースに変換します。
Preview
Detailed feature comparison
| Feature | ClickHouse | SheetQuery |
|---|---|---|
| 主要カテゴリー | データベース | データベース |
| 追加日 | 2025-08-01 | 2025-08-11 |
| 価格 | フリーミアム | 有料 |
| 公式サイト | clickhouse.com | sheetquery.com |
| 製品タイプ | ウェブサイト | ブラウザ拡張 |
| 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 | 786.3K | 643 |
| 月間成長率 | 2.8% | 383.5% |
| お気に入り | 105 | 101 |
| Details | 詳細を見る | 詳細を見る |
ClickHouse vs SheetQuery monthly traffic
Compare ClickHouse and SheetQuery by monthly reach, traffic trend, visit depth, top regions, and acquisition sources.
How to interpret the traffic data
In the ClickHouse vs SheetQuery monthly traffic comparison, ClickHouse currently shows 786.3K visits and SheetQuery shows 643; ClickHouse has about 1,222.8 times the visible traffic of SheetQuery, an absolute difference of about 785.6K 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.
ClickHouse monthly traffic:
Latest traffic
月間訪問数
786.3K
平均滞在時間
1:49
訪問あたりページ数
2.77
直帰率
49.31%
Data updated 2026-06-15
Monthly traffic trend
- 2025/9: 838.4K 月間訪問数
- 2026/1: 905.2K 月間訪問数
- 2026/2: 730.9K 月間訪問数
- 2026/3: 771.1K 月間訪問数
- 2026/4: 764.9K 月間訪問数
- 2026/5: 786.3K 月間訪問数
主要地域
Top 5 countries/regions
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇺🇸United States | 29.07% | 228.6K |
| 🇨🇳China | 21.93% | 172.4K |
| 🇮🇳India | 20.75% | 163.2K |
| 🇷🇺Russia | 20.01% | 157.3K |
| 🇹🇷Turkey | 8.24% | 64.8K |
流入元
| Source type | Percentage | Traffic |
|---|---|---|
| ダイレクト | 76.16% | 598.8K |
| 参照元 | 22.42% | 176.3K |
| Eメール | 1.42% | 11.2K |
検索キーワード
click houseclickhouseclickhouse careersclickhouse databaseclickhousedb
SheetQuery monthly traffic:
Latest traffic
月間訪問数
643
平均滞在時間
0:00
訪問あたりページ数
1.01
直帰率
31.93%
Data updated 2026-06-15
Monthly traffic trend
- 2025/8: 84 月間訪問数
- 2025/9: 349 月間訪問数
- 2026/3: 0 月間訪問数
- 2026/4: 133 月間訪問数
- 2026/5: 643 月間訪問数
主要地域
Top 5 countries/regions
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇲🇾Malaysia | 91.26% | 587 |
| 🇮🇳India | 8.74% | 56 |
検索キーワード
how to show departmentwise salary distribution in google sheetssheetquery
Traffic-based selection guidance: If public market visibility is an important first-pass criterion, investigate ClickHouse 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 ClickHouse and SheetQuery
ClickHouse Core features
データベース
可観測性
SheetQuery Core features
データベース
スプレッドシート
Use cases
ClickHouse Use cases
データ分析
データベース
SQL
ビッグデータ
ビジネスインテリジェンス
データウェアハウス
機械学習
可観測性
OLAP
オープンソース
リアルタイム分析
SheetQuery Use cases
データ分析
データベース
SQL
API連携
自動化
一括更新
データ処理
Google スプレッドシート
スプレッドシート
ClickHouse vs SheetQuery：In-depth comparison and selection guidance
First decide whether the products solve the same kind of need
This in-depth ClickHouse vs SheetQuery comparison uses only the product records, taxonomy, audience, traffic, and community signals available on this page. ClickHouse is primarily listed under “データベース”, while SheetQuery is primarily listed under “データベース”, so the first decision is whether your actual task matches their recorded scope.
The structured fields currently show these decision-relevant differences: Product type (ClickHouse: Website; SheetQuery: Browser extension); Pricing (ClickHouse: Freemium; SheetQuery: Paid); Monthly visits (ClickHouse: 786.3K; SheetQuery: 643); Monthly growth (ClickHouse: 2.8%; SheetQuery: 383.5%); Favorites (ClickHouse: 105; SheetQuery: 101). These facts are more useful for selection than brand visibility alone.
What market visibility and monthly traffic mean
In the ClickHouse vs SheetQuery monthly traffic comparison, ClickHouse currently shows 786.3K visits and SheetQuery shows 643; ClickHouse has about 1,222.8 times the visible traffic of SheetQuery, an absolute difference of about 785.6K 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 ClickHouse 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
ClickHouse and SheetQuery currently overlap in shared categories: データベース; shared tags: データ分析、データベース、SQL. This can place both on the same shortlist, but it does not prove equal implementation, depth, or cost.
ClickHouse's unique categories/tags are 可観測性、ビッグデータ、ビジネスインテリジェンス、データウェアハウス、機械学習、OLAP、オープンソース、リアルタイム分析; SheetQuery's are スプレッドシート、API連携、自動化、一括更新、データ処理、Google スプレッドシート. 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
ClickHouse has no verified rating, 0 comments, 105 favorites, and 103 likes；SheetQuery has no verified rating, 0 comments, 101 favorites, and 99 likes。
Neither product has enough rating or comment samples for a credible reputation ranking.
Selection guidance by actual need
When to evaluate ClickHouse first
Put ClickHouse on the priority trial list when the task aligns with “データベース” and especially 可観測性、ビッグデータ、ビジネスインテリジェンス、データウェアハウス、機械学習、OLAP. This follows recorded positioning and does not imply unlisted capabilities are absent.
ClickHouse also currently records: pricing is freemium, product type is website, 786.3K 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 SheetQuery first
Put SheetQuery on the priority trial list when the task aligns with “データベース” and especially スプレッドシート、API連携、自動化、一括更新、データ処理、Google スプレッドシート. This follows recorded positioning and does not imply unlisted capabilities are absent.
SheetQuery also currently records: pricing is paid, product type is browser extension, 643 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 ClickHouse and SheetQuery, 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 ClickHouse and SheetQuery?
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.