ClickHouse는 고성능 오픈소스 컬럼 기반 OLAP 데이터베이스 관리 시스템입니다. 대규모 데이터의 실시간 분석을 위해 설계되었으며, 관찰 가능성, 비즈니스 인텔리전스, ML/GenAI 등을 위한 초고속 쿼리를 지원하면서도 리소스 효율성과 비용 효율성을 유지합니다.
Google Sheets에서 직접 고급 SQL 쿼리를 실행하여 정교한 데이터 분석, 대량 업데이트, 삭제 및 삽입을 수행할 수 있는 강력한 도구입니다. 스프레드시트를 쿼리 가능한 데이터베이스로 변환하세요.
제품 개요
ClickHouse 제품 개요
ClickHouse는 고성능 오픈소스 컬럼 기반 OLAP 데이터베이스 관리 시스템입니다. 대규모 데이터의 실시간 분석을 위해 설계되었으며, 관찰 가능성, 비즈니스 인텔리전스, ML/GenAI 등을 위한 초고속 쿼리를 지원하면서도 리소스 효율성과 비용 효율성을 유지합니다.
SheetQuery 제품 개요
Google Sheets에서 직접 고급 SQL 쿼리를 실행하여 정교한 데이터 분석, 대량 업데이트, 삭제 및 삽입을 수행할 수 있는 강력한 도구입니다. 스프레드시트를 쿼리 가능한 데이터베이스로 변환하세요.
Detailed feature comparison
| Feature | ClickHouse | SheetQuery |
|---|---|---|
| 주요 카테고리 | 데이터베이스 | 데이터베이스 |
| 등록일 | 2025-08-01 | 2025-08-11 |
| 가격 | 프리미엄 | 유료 |
| 공식 사이트 | clickhouse.com | sheetquery.com |
| 제품 유형 | 웹사이트 | 브라우저 확장 |
| Performance data | ||
| 사용자 평점 | 확인되지 않음 | 확인되지 않음 |
| 댓글 | 0 | 0 |
| 월 방문 | 786.3K | 643 |
| 월 성장률 | 2.8% | 383.5% |
| 즐겨찾기 | 105 | 101 |
| Details | 상세 보기 | 상세 보기 |
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
Monthly traffic trend
- 2025/9: 838.4K 월 방문
- 2026/1: 905.2K 월 방문
- 2026/2: 730.9K 월 방문
- 2026/3: 771.1K 월 방문
- 2026/4: 764.9K 월 방문
- 2026/5: 786.3K 월 방문
주요 지역
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 |
트래픽 소스
| Source type | Percentage | Traffic |
|---|---|---|
| 직접 | 76.16% | 598.8K |
| 리퍼럴 | 22.42% | 176.3K |
| 이메일 | 1.42% | 11.2K |
검색 키워드
SheetQuery monthly traffic:
Latest traffic
Monthly traffic trend
- 2025/8: 84 월 방문
- 2025/9: 349 월 방문
- 2026/3: 0 월 방문
- 2026/4: 133 월 방문
- 2026/5: 643 월 방문
주요 지역
Top 5 countries/regions
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇲🇾Malaysia | 91.26% | 587 |
| 🇮🇳India | 8.74% | 56 |
검색 키워드
Usage comparison
Compare the core capabilities of ClickHouse and SheetQuery
ClickHouse Core features
SheetQuery Core features
Use cases
ClickHouse Use cases
SheetQuery Use cases
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 “데이터베이스”, while SheetQuery is primarily listed under “데이터베이스”, 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: 데이터베이스; shared tags: 데이터 분석, 데이터베이스 및 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 관측 가능성, 빅데이터, 비즈니스 인텔리전스, 데이터 웨어하우스, 기계 학습, OLAP, 오픈 소스 및 실시간 분석; SheetQuery's are 스프레드시트, API 통합, 자동화, 일괄 업데이트, 데이터 처리 및 Google 시트. 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 “데이터베이스” and especially 관측 가능성, 빅데이터, 비즈니스 인텔리전스, 데이터 웨어하우스, 기계 학습 및 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 “데이터베이스” and especially 스프레드시트, API 통합, 자동화, 일괄 업데이트, 데이터 처리 및 Google 시트. 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.




