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csvgetter
Base de datos · 5.9K visitas mensuales

csvgetter es una herramienta de automatización sin código diseñada para facilitar la exportación de datos y las copias de seguridad desde plataformas SaaS populares. Permite a los usuarios programar y automatizar la extracción de datos de servicios como Airtable, Stripe y Notion, entregándolos en formatos accesibles como CSV y JSON. Esto garantiza la seguridad de los datos, facilita el análisis y evita la dependencia de un proveedor.

VS
Make
CRM · 6.7M visitas mensuales

Make es una potente plataforma visual que te permite diseñar, construir y automatizar cualquier cosa, desde tareas simples hasta flujos de trabajo complejos, sin código. Conecta miles de aplicaciones y servicios, incluidas herramientas avanzadas de IA como OpenAI y Google Gemini, permitiéndote crear automatizaciones inteligentes y agentes de IA para optimizar tus operaciones comerciales, marketing, ventas y más.

csvgetter vs Make: precios, funciones y tráfico

Compara csvgetter y Make por posicionamiento, precio, capacidades, tráfico y opiniones.

Actualizado 5 ago 2026

Resumen del producto

csvgetter Resumen del producto

csvgetter es una herramienta de automatización sin código diseñada para facilitar la exportación de datos y las copias de seguridad desde plataformas SaaS populares. Permite a los usuarios programar y automatizar la extracción de datos de servicios como Airtable, Stripe y Notion, entregándolos en formatos accesibles como CSV y JSON. Esto garantiza la seguridad de los datos, facilita el análisis y evita la dependencia de un proveedor.

Preview

Make Resumen del producto

Make es una potente plataforma visual que te permite diseñar, construir y automatizar cualquier cosa, desde tareas simples hasta flujos de trabajo complejos, sin código. Conecta miles de aplicaciones y servicios, incluidas herramientas avanzadas de IA como OpenAI y Google Gemini, permitiéndote crear automatizaciones inteligentes y agentes de IA para optimizar tus operaciones comerciales, marketing, ventas y más.

Preview

Detailed feature comparison

FeaturecsvgetterMake
Categoría principalBase de datosCRM
Añadido2025-08-012025-08-08
PrecioFreemiumFreemium
Sitio oficialwww.csvgetter.comwww.make.com
Tipo de productoSitio webSitio web
Performance data
ValoraciónSin verificarSin verificar
Comentarios00
Visitas mensuales5.9K6.7M
Crecimiento mensual-23.7%12.7%
Favoritos135122
DetailsVer detallesVer detalles

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

Visitas mensuales
5.9K
Duración media
0:30
Páginas por visita
2.5
Tasa de rebote
39.23%
Data updated 2026-06-15

Monthly traffic trend

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

Regiones principales

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

Palabras clave

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

Make monthly traffic:

Latest traffic

Visitas mensuales
6.7M
Duración media
7:28
Páginas por visita
8.43
Tasa de rebote
32.56%
Data updated 2026-06-15

Monthly traffic trend

  • 2026/1: 5.4M Visitas mensuales
  • 2026/2: 5M Visitas mensuales
  • 2026/3: 6.1M Visitas mensuales
  • 2026/4: 5.9M Visitas mensuales
  • 2026/5: 6.7M Visitas mensuales

Regiones principales

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

Fuentes de tráfico

Source typePercentageTraffic
Directo90.82%6.1M
Referido6.17%412.7K
Correo electrónico3.01%201.3K

Palabras clave

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

Sin Código
Automatización
Base de datos

Make Core features

Sin Código
Automatización
CRM
Automatización de Marketing

Use cases

csvgetter Use cases

automatización
No-code
Airtable
Respaldo
CSV
exportación de datos
Integración de datos
JSON
Notion
Stripe

Make Use cases

automatización
No-code
Agente de IA
API
Chatbot
Sincronización de datos
integración
iPaaS
Automatización de marketing
productividad
flujo de trabajo

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 datos”, 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 datos; 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: Sin Código y Automatización; shared tags: automatización y 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 datos, Airtable, Respaldo, CSV, exportación de datos, Integración de datos, JSON y Notion; Make's are CRM, Automatización de Marketing, Agente de IA, API, Chatbot, Sincronización de datos, integración e 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 datos” and especially Base de datos, Airtable, Respaldo, CSV, exportación de datos e Integración de datos. 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, Automatización de Marketing, Agente de IA, API, Chatbot y Sincronización de datos. 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.

Preguntas frecuentes

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.