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csvgetter
Base de données · 5.9K visites mensuelles

csvgetter est un outil d'automatisation sans code conçu pour faciliter l'exportation de données et les sauvegardes à partir de plateformes SaaS populaires. Il permet aux utilisateurs de planifier et d'automatiser l'extraction de données de services comme Airtable, Stripe et Notion, en les livrant dans des formats accessibles comme CSV et JSON. Cela garantit la sécurité des données, facilite l'analyse et empêche le verrouillage par le fournisseur.

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VS
Make
CRM · 6.7M visites mensuelles

Make est une puissante plateforme visuelle qui vous permet de concevoir, construire et automatiser n'importe quoi, des tâches simples aux flux de travail complexes, sans code. Elle connecte des milliers d'applications et de services, y compris des outils d'IA avancés comme OpenAI et Google Gemini, vous permettant de créer des automatisations intelligentes et des agents IA pour rationaliser vos opérations commerciales, marketing, ventes, et plus encore.

Visiter le siteVoir les détails

csvgetter vs Make : prix, fonctions et trafic

Comparez csvgetter et Make selon leur positionnement, prix, fonctions, trafic et avis.

Mis à jour 5 août 2026

Aperçu du produit

csvgetter Aperçu du produit

csvgetter est un outil d'automatisation sans code conçu pour faciliter l'exportation de données et les sauvegardes à partir de plateformes SaaS populaires. Il permet aux utilisateurs de planifier et d'automatiser l'extraction de données de services comme Airtable, Stripe et Notion, en les livrant dans des formats accessibles comme CSV et JSON. Cela garantit la sécurité des données, facilite l'analyse et empêche le verrouillage par le fournisseur.

Preview

Make Aperçu du produit

Make est une puissante plateforme visuelle qui vous permet de concevoir, construire et automatiser n'importe quoi, des tâches simples aux flux de travail complexes, sans code. Elle connecte des milliers d'applications et de services, y compris des outils d'IA avancés comme OpenAI et Google Gemini, vous permettant de créer des automatisations intelligentes et des agents IA pour rationaliser vos opérations commerciales, marketing, ventes, et plus encore.

Preview

Detailed feature comparison

FeaturecsvgetterMake
Catégorie principaleBase de donnéesCRM
Ajouté2025-08-012025-08-08
TarificationFreemiumFreemium
Site officielwww.csvgetter.comwww.make.com
Type de produitSite webSite web
Performance data
Note utilisateurNon vérifiéNon vérifié
Commentaires00
Visites mensuelles5.9K6.7M
Croissance mensuelle-23.7%12.7%
Favoris135122
DetailsVoir les détailsVoir les détails

csvgetter vs Make monthly traffic

Compare csvgetter and Make by monthly reach, traffic trend, visit depth, top regions, and acquisition sources.

How to interpret the traffic data

In the csvgetter vs Make monthly traffic comparison, csvgetter currently shows 5.9K visits and Make shows 6.7M; Make has about 1,127.3 times the visible traffic of csvgetter, an absolute difference of about 6.7M 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.

Make is registered at the www.make.com/en subpage. Because the current data does not state whether other host pages are excluded, treat this as domain-level context rather than independent traffic for one product or project.

csvgetter monthly traffic:

Latest traffic

Visites mensuelles
5.9K
Durée moyenne
0:30
Pages par visite
2.5
Taux de rebond
39.23%
Data updated 2026-06-15

Monthly traffic trend

  • 2025/9: 14.3K Visites mensuelles
  • 2026/1: 15.5K Visites mensuelles
  • 2026/2: 7.2K Visites mensuelles
  • 2026/3: 6.9K Visites mensuelles
  • 2026/4: 7.8K Visites mensuelles
  • 2026/5: 5.9K Visites mensuelles

Principales régions

Top 5 countries/regions
Country/regionPercentageTraffic
🇺🇸United States49.17%2.9K
🇮🇳India18.01%1.1K
🇫🇷France14.73%874
🇮🇹Italy13.1%777
🇳🇱Netherlands4.99%296

Mots-clés

csvgettercsv to apidownload notion database to csvdownload notion page as excelexport notion to google sheets

Make monthly traffic:

Latest traffic

Visites mensuelles
6.7M
Durée moyenne
7:28
Pages par visite
8.43
Taux de rebond
32.56%
Data updated 2026-06-15

Monthly traffic trend

  • 2026/1: 5.4M Visites mensuelles
  • 2026/2: 5M Visites mensuelles
  • 2026/3: 6.1M Visites mensuelles
  • 2026/4: 5.9M Visites mensuelles
  • 2026/5: 6.7M Visites mensuelles

Principales régions

Top 5 countries/regions
Country/regionPercentageTraffic
🇺🇸United States40.62%2.7M
🇮🇳India19.69%1.3M
🇫🇷France18.85%1.3M
🇩🇪Germany11.09%741.7K
🇮🇱Israel9.75%652.1K

Sources de trafic

Source typePercentageTraffic
Direct90.82%6.1M
Référence6.17%412.7K
E-mail3.01%201.3K

Mots-clés

gemini aimakemake aimake.comn8n
Traffic-based selection guidance: Make is registered under a www.make.com subpath, so its large visible total may include the host platform. The current data does not justify choosing Make for traffic alone; shortlist by unique taxonomy and use case, then validate with the same tasks.

Usage comparison

Compare the core capabilities of csvgetter and Make

csvgetter Core features

Sans Code
Automatisation
Base de données

Make Core features

Sans Code
Automatisation
CRM
Automatisation du marketing

Use cases

csvgetter Use cases

automatisation
No-code
Airtable
Sauvegarde
CSV
exportation de données
Intégration de données
JSON
Notion
Stripe

Make Use cases

automatisation
No-code
Agent IA
API
Chatbot
Synchronisation des données
intégration
iPaaS
Automatisation du marketing
productivité
flux de travail

csvgetter vs Make：In-depth comparison and selection guidance

First decide whether the products solve the same kind of need

This in-depth csvgetter vs Make comparison uses only the product records, taxonomy, audience, traffic, and community signals available on this page. csvgetter is primarily listed under “Base de données”, while Make is primarily listed under “CRM”, so the first decision is whether your actual task matches their recorded scope.

The structured fields currently show these decision-relevant differences: Primary category (csvgetter: Base de données; Make: CRM); Monthly visits (csvgetter: 5.9K; Make: 6.7M); Monthly growth (csvgetter: -23.7%; Make: 12.7%); Favorites (csvgetter: 135; Make: 122); Website (csvgetter: www.csvgetter.com; Make: www.make.com). These facts are more useful for selection than brand visibility alone.

What market visibility and monthly traffic mean

In the csvgetter vs Make monthly traffic comparison, csvgetter currently shows 5.9K visits and Make shows 6.7M; Make has about 1,127.3 times the visible traffic of csvgetter, an absolute difference of about 6.7M 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.

Make is registered at the www.make.com/en subpage. Because the current data does not state whether other host pages are excluded, treat this as domain-level context rather than independent traffic for one product or project.

Make is registered under a www.make.com subpath, so its large visible total may include the host platform. The current data does not justify choosing Make for traffic alone; shortlist by unique taxonomy and use case, then validate with the same tasks.

Product positioning, use cases, and roles

csvgetter and Make currently overlap in shared categories: Sans Code et Automatisation; shared tags: automatisation et No-code. This can place both on the same shortlist, but it does not prove equal implementation, depth, or cost.

csvgetter's unique categories/tags are Base de données, Airtable, Sauvegarde, CSV, exportation de données, Intégration de données, JSON et Notion; Make's are CRM, Automatisation du marketing, Agent IA, API, Chatbot, Synchronisation des données, intégration et iPaaS. 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

csvgetter has no verified rating, 0 comments, 135 favorites, and 129 likes；Make has no verified rating, 0 comments, 122 favorites, and 125 likes。

Neither product has enough rating or comment samples for a credible reputation ranking.

Selection guidance by actual need

When to evaluate csvgetter first

Put csvgetter on the priority trial list when the task aligns with “Base de données” and especially Base de données, Airtable, Sauvegarde, CSV, exportation de données et Intégration de données. This follows recorded positioning and does not imply unlisted capabilities are absent.

csvgetter also currently records: pricing is freemium, product type is website, 5.9K 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 Make first

Put Make on the priority trial list when the task aligns with “CRM” and especially CRM, Automatisation du marketing, Agent IA, API, Chatbot et Synchronisation des données. This follows recorded positioning and does not imply unlisted capabilities are absent.

Make also currently records: pricing is freemium, product type is website, 6.7M monthly visits shown for the registered host (subpage scope unknown), 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 csvgetter and Make, 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.

FAQ comparative

How should I choose between csvgetter and Make?
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.