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Streamlit
Datenvisualisierung · 918.5K monatliche besuche

Streamlit ist ein Open-Source-Python-Framework, das es Entwicklern und Datenwissenschaftlern ermöglicht, in wenigen Minuten ansprechende, benutzerdefinierte Web-Apps für maschinelles Lernen und Datenwissenschaft zu erstellen und zu teilen. Die Streamlit Community Cloud bietet eine kostenlose Plattform zum Bereitstellen, Verwalten und Teilen dieser öffentlichen Anwendungen mit der Welt und fördert so eine kollaborative Umgebung für Innovationen.

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victordibia
Datenvisualisierung · 22.4K monatliche besuche

Ein umfassender Ressourcen-Hub von Victor Dibia, einem führenden Forscher in Angewandtem ML und HCI. Er bietet Open-Source-KI-Tools wie AutoGen Studio und LIDA, tiefgehende Artikel, Forschungsarbeiten und Vorträge zu generativer KI, Multi-Agenten-Systemen und Mensch-Computer-Interaktion. Eine wertvolle Plattform für Entwickler, Forscher und KI-Enthusiasten.

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Streamlit vs victordibia: Preise, Funktionen und Traffic

Vergleiche Streamlit und victordibia nach Positionierung, Preis, Funktionen, Traffic und Nutzerfeedback.

Aktualisiert 05.08.2026

Produktübersicht

Streamlit Produktübersicht

Streamlit ist ein Open-Source-Python-Framework, das es Entwicklern und Datenwissenschaftlern ermöglicht, in wenigen Minuten ansprechende, benutzerdefinierte Web-Apps für maschinelles Lernen und Datenwissenschaft zu erstellen und zu teilen. Die Streamlit Community Cloud bietet eine kostenlose Plattform zum Bereitstellen, Verwalten und Teilen dieser öffentlichen Anwendungen mit der Welt und fördert so eine kollaborative Umgebung für Innovationen.

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victordibia Produktübersicht

Ein umfassender Ressourcen-Hub von Victor Dibia, einem führenden Forscher in Angewandtem ML und HCI. Er bietet Open-Source-KI-Tools wie AutoGen Studio und LIDA, tiefgehende Artikel, Forschungsarbeiten und Vorträge zu generativer KI, Multi-Agenten-Systemen und Mensch-Computer-Interaktion. Eine wertvolle Plattform für Entwickler, Forscher und KI-Enthusiasten.

Preview

Detailed feature comparison

FeatureStreamlitvictordibia
HauptkategorieDatenvisualisierungDatenvisualisierung
Hinzugefügt2025-08-172025-08-04
PreismodellFreemiumKostenlos
Offizielle Websiteshare.streamlit.iovictordibia.com
ProdukttypWebsiteWebsite
Performance data
NutzerbewertungNicht verifiziertNicht verifiziert
Kommentare00
Monatliche Besuche918.5K22.4K
Monatliches Wachstum6.5%33.6%
Favoriten125128
DetailsDetails ansehenDetails ansehen

Streamlit vs victordibia monthly traffic

Compare Streamlit and victordibia by monthly reach, traffic trend, visit depth, top regions, and acquisition sources.

How to interpret the traffic data

In the Streamlit vs victordibia monthly traffic comparison, Streamlit currently shows 918.5K visits and victordibia shows 22.4K; Streamlit has about 41 times the visible traffic of victordibia, an absolute difference of about 896.1K 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.

Streamlit monthly traffic:

Latest traffic

Monatliche Besuche
918.5K
Ø Besuchsdauer
3:29
Seiten pro Besuch
3.41
Absprungrate
56.87%
Data updated 2026-06-15

Monthly traffic trend

  • 2025/9: 501.6K Monatliche Besuche
  • 2026/1: 717.2K Monatliche Besuche
  • 2026/2: 702.3K Monatliche Besuche
  • 2026/3: 847.5K Monatliche Besuche
  • 2026/4: 862.8K Monatliche Besuche
  • 2026/5: 918.5K Monatliche Besuche

Top-Regionen

Top 5 countries/regions
Country/regionPercentageTraffic
🇺🇸United States44.68%410.4K
🇮🇳India25.68%235.9K
🇰🇷Korea, Republic of12.59%115.6K
🇬🇧United Kingdom8.9%81.7K
🇵🇰Pakistan8.15%74.9K

Traffic-Quellen

Source typePercentageTraffic
Direkt57.82%531.1K
Verweis40.37%370.8K
E-Mail1.81%16.6K

Suchbegriffe

share.streamlitstreamlitstreamlit cloudstreamlit community cloudstreamlit login

victordibia monthly traffic:

Latest traffic

Monatliche Besuche
22.4K
Ø Besuchsdauer
0:22
Seiten pro Besuch
1.61
Absprungrate
39.19%
Data updated 2026-06-15

Monthly traffic trend

  • 2025/9: 13.3K Monatliche Besuche
  • 2026/1: 12.2K Monatliche Besuche
  • 2026/2: 11.6K Monatliche Besuche
  • 2026/3: 11.2K Monatliche Besuche
  • 2026/4: 16.8K Monatliche Besuche
  • 2026/5: 22.4K Monatliche Besuche

Top-Regionen

Top 5 countries/regions
Country/regionPercentageTraffic
🇺🇸United States37.7%8.5K
🇮🇳India25.61%5.7K
🇻🇳Vietnam14.63%3.3K
🇬🇧United Kingdom11.38%2.6K
🇮🇩Indonesia10.68%2.4K

Suchbegriffe

anthropic designblender export to react fiberclaude.ai/designclaude designhandtrack.js
Traffic-based selection guidance: If public market visibility is an important first-pass criterion, investigate Streamlit 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 Streamlit and victordibia

Streamlit Core features

Datenvisualisierung
Low-Code No-Code
App-Baukasten

victordibia Core features

Datenvisualisierung
Low-Code No-Code
Forschung
Schreiben

Use cases

Streamlit Use cases

Datenvisualisierung
Entwicklerwerkzeuge
maschinelles Lernen
Open Source
App-Baukasten
Dashboard
Datenwissenschaft
Python
Web-App

victordibia Use cases

Datenvisualisierung
Entwicklerwerkzeuge
maschinelles Lernen
Open Source
KI-Bildung
KI-Forschung
AutoGen
Generative KI
Mensch-Computer-Interaktion
Multi-Agenten-Systeme

Streamlit vs victordibia：In-depth comparison and selection guidance

First decide whether the products solve the same kind of need

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

The structured fields currently show these decision-relevant differences: Pricing (Streamlit: Freemium; victordibia: Free); Monthly visits (Streamlit: 918.5K; victordibia: 22.4K); Monthly growth (Streamlit: 6.5%; victordibia: 33.6%); Favorites (Streamlit: 125; victordibia: 128); Website (Streamlit: share.streamlit.io; victordibia: victordibia.com). These facts are more useful for selection than brand visibility alone.

What market visibility and monthly traffic mean

In the Streamlit vs victordibia monthly traffic comparison, Streamlit currently shows 918.5K visits and victordibia shows 22.4K; Streamlit has about 41 times the visible traffic of victordibia, an absolute difference of about 896.1K 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 Streamlit 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

Streamlit and victordibia currently overlap in shared categories: Datenvisualisierung und Low-Code No-Code; shared tags: Datenvisualisierung, Entwicklerwerkzeuge, maschinelles Lernen und Open Source. This can place both on the same shortlist, but it does not prove equal implementation, depth, or cost.

Streamlit's unique categories/tags are App-Baukasten, Dashboard, Datenwissenschaft, Python und Web-App; victordibia's are Forschung, Schreiben, KI-Bildung, KI-Forschung, AutoGen, Generative KI, Mensch-Computer-Interaktion und Multi-Agenten-Systeme. 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

Streamlit has no verified rating, 0 comments, 125 favorites, and 125 likes；victordibia has no verified rating, 0 comments, 128 favorites, and 120 likes。

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

Selection guidance by actual need

When to evaluate Streamlit first

Put Streamlit on the priority trial list when the task aligns with “Datenvisualisierung” and especially App-Baukasten, Dashboard, Datenwissenschaft, Python und Web-App. This follows recorded positioning and does not imply unlisted capabilities are absent.

Streamlit also currently records: pricing is freemium, product type is website, 918.5K 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 victordibia first

Put victordibia on the priority trial list when the task aligns with “Datenvisualisierung” and especially Forschung, Schreiben, KI-Bildung, KI-Forschung, AutoGen und Generative KI. This follows recorded positioning and does not imply unlisted capabilities are absent.

victordibia also currently records: pricing is free, product type is website, 22.4K 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 Streamlit and victordibia, 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.

Vergleichs-FAQ

How should I choose between Streamlit and victordibia?
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.