ClickHouse ist ein leistungsstarkes, quelloffenes, spaltenorientiertes OLAP-Datenbankmanagementsystem. Es ist für Echtzeitanalysen großer Datenmengen konzipiert und ermöglicht blitzschnelle Abfragen für Observability, Business Intelligence, ML/GenAI und mehr, während es ressourceneffizient und kostengünstig bleibt.
Ein leistungsstarkes Tool, mit dem Sie erweiterte SQL-Abfragen direkt in Google Sheets für anspruchsvolle Datenanalysen, Massenaktualisierungen, -löschungen und -einfügungen ausführen können. Verwandeln Sie Ihre Tabellenkalkulationen in eine abfragbare Datenbank.
ClickHouse ist ein leistungsstarkes, quelloffenes, spaltenorientiertes OLAP-Datenbankmanagementsystem. Es ist für Echtzeitanalysen großer Datenmengen konzipiert und ermöglicht blitzschnelle Abfragen für Observability, Business Intelligence, ML/GenAI und mehr, während es ressourceneffizient und kostengünstig bleibt.
Ein leistungsstarkes Tool, mit dem Sie erweiterte SQL-Abfragen direkt in Google Sheets für anspruchsvolle Datenanalysen, Massenaktualisierungen, -löschungen und -einfügungen ausführen können. Verwandeln Sie Ihre Tabellenkalkulationen in eine abfragbare Datenbank.
| Feature | ClickHouse | SheetQuery |
|---|---|---|
| Hauptkategorie | Datenbanken | Datenbanken |
| Hinzugefügt | 2025-08-01 | 2025-08-11 |
| Preismodell | Freemium | Kostenpflichtig |
| Offizielle Website | clickhouse.com | sheetquery.com |
| Produkttyp | Website | Browser-Erweiterung |
| Performance data | ||
| Nutzerbewertung | Nicht verifiziert | Nicht verifiziert |
| Kommentare | 0 | 0 |
| Monatliche Besuche | 786.3K | 643 |
| Monatliches Wachstum | 2.8% | 383.5% |
| Favoriten | 105 | 101 |
| Details | Details ansehen | Details ansehen |
Compare ClickHouse and SheetQuery by monthly reach, traffic trend, visit depth, top regions, and acquisition sources.
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.
| 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 |
| Source type | Percentage | Traffic |
|---|---|---|
| Direkt | 76.16% | 598.8K |
| Verweis | 22.42% | 176.3K |
| 1.42% | 11.2K |
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇲🇾Malaysia | 91.26% | 587 |
| 🇮🇳India | 8.74% | 56 |
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 “Datenbanken”, while SheetQuery is primarily listed under “Datenbanken”, 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.
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.
ClickHouse and SheetQuery currently overlap in shared categories: Datenbanken; shared tags: Datenanalyse, Datenbank und 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 Beobachtbarkeit, Big Data, Business Intelligence, Data Warehouse, maschinelles Lernen, OLAP, Open Source und Echtzeitanalyse; SheetQuery's are Tabellenkalkulationen, API-Integration, Automatisierung, Massenaktualisierung, Datenverarbeitung, Google Tabellen und Tabellenkalkulation. These unique fields are the strongest differentiators: validate the product whose recorded scope matches the task instead of following traffic alone.
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.
Put ClickHouse on the priority trial list when the task aligns with “Datenbanken” and especially Beobachtbarkeit, Big Data, Business Intelligence, Data Warehouse, maschinelles Lernen und 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.
Put SheetQuery on the priority trial list when the task aligns with “Datenbanken” and especially Tabellenkalkulationen, API-Integration, Automatisierung, Massenaktualisierung, Datenverarbeitung und Google Tabellen. 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.
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.
