Software Alternatives & Startups

Data Miner VS Streamlit

Compare Data Miner VS Streamlit and see what are their differences

Data Miner

Data Miner is a Google Chrome extension that helps you scrape data from web pages and into a CSV file or Excel spreadsheet.

Rating
0 reviews
Streamlit

Turn python scripts into beautiful ML tools

Rating
0 reviews
Pricing
Open source
Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Which is more popular?

Based on our record, Streamlit seems to be a lot more popular than Data Miner. While we know about 220 links to Streamlit, we've tracked only 7 mentions of Data Miner.

social mentions
7 vs 220
Web Scraping popularity
100% vs 0%
alternatives listed
135 vs 240+

Base details

Website, pricing, platforms and company facts side by side.

Data Miner
Streamlit
Website dataminer.io streamlit.io
Pricing
Open source Official pricing
Listed in

Features and specs

What each product offers, as listed by its team.

Data Miner 7 features
Streamlit 5 features
  • User-Friendly Interface
    Data Miner offers a clean and intuitive user interface that allows users to easily navigate and set up web scraping tasks without requiring extensive technical knowledge.
  • Browser Extension
    Being available as a browser extension for both Chrome and Edge makes it easy to install and use directly within the browser, without needing separate software installations.
  • Pre-built Recipes
    Data Miner provides a library of pre-built recipes for common web scraping tasks, enabling users to quickly deploy scrapers without starting from scratch.
  • Custom Recipes
    Users have the option to create custom recipes, offering flexibility and the ability to tailor scraping tasks to specific needs.
  • Cloud Storage
    Offers cloud storage options that allow users to save and manage their scraped data directly on the platform for easy access and organization.
  • Export Options
    Supports multiple export formats like CSV, XLS, and Google Sheets, making it easy for users to integrate scraped data with other tools and workflows.
  • Scheduling
    Allows users to schedule scraping tasks, automating the data collection process at specified intervals.

Possible disadvantages

  • Limited Free Tier
    The free version of Data Miner is limited in terms of the number of rows and pages that can be scraped, which may not be sufficient for more extensive data collection needs.
  • Learning Curve
    While the interface is user-friendly, there can still be a learning curve for users unfamiliar with web scraping concepts and the tool itself.
  • Browser Dependence
    As Data Miner is a browser extension, its functionality is limited to the browser environment, which might not be ideal for more complex or large-scale web scraping tasks.
  • Potential Website Restrictions
    Some websites actively prevent scraping activities, which could limit the effectiveness of Data Miner on certain web pages.
  • Subscription Cost
    Advanced features and higher usage requirements necessitate a subscription plan, which may be costly for individual users or small businesses.
  • Reliance on Internet Stability
    As an online tool, its performance can be hindered by poor internet connectivity, potentially disrupting the scraping process.
  • Ease of Use
    Streamlit's API is extremely intuitive and easy to learn, which makes it accessible for developers of varying experience levels. The simplicity allows for rapid development and less time spent on complex front-end coding.
  • Interactive Widgets
    It provides a set of interactive widgets that make it simple to add complex functionalities like sliders, buttons, and file uploaders to your application with minimal code.
  • Real-time Feedback
    Streamlit supports real-time data updates, allowing users to see changes instantly. This is particularly useful for data analysis and machine learning applications where live data visualization is crucial.
  • Integration with Machine Learning Libraries
    Streamlit integrates seamlessly with popular machine learning libraries like TensorFlow, PyTorch, and scikit-learn, making it a great tool for showcasing machine learning models and results.
  • Open Source
    Being an open-source project, Streamlit is free to use and comes with the support and contributions of an active community. This means continuous improvements and a wealth of shared resources.

Possible disadvantages

  • Limited Customization
    Streamlit offers limited customization options compared to traditional web frameworks. This can be a hindrance if you need a highly customized UI/UX for your application.
  • Performance Issues
    For more complex or resource-intensive applications, Streamlit may suffer from performance drawbacks. It is not designed for high-performance computing out of the box.
  • Scalability
    Streamlit is not well-suited for large-scale applications requiring major backend architecture or for scenarios demanding high scalability and concurrency.
  • Limited Widget Style Options
    The styling and customization options for widgets are somewhat limited, meaning your application's look and feel might be more constrained compared to using other front-end frameworks.
  • Deployment Complexity
    While Streamlit provides some deployment options, deploying Streamlit apps in a production environment can sometimes require additional effort and knowledge, especially for those unfamiliar with web deployment practices.

Analysis

An editorial look at what each product does well and who it suits.

Data Miner
Streamlit

Overall verdict

  • Data Miner is generally considered a good tool for individuals and businesses that need to quickly and easily extract large amounts of data from websites without the need for advanced technical skills. It is appreciated for its ease of use and effectiveness in various scenarios.

Why this product is good

  • Data Miner (dataminer.io) is a web scraping tool that allows users to extract data from websites into various formats such as CSV or Excel. It is known for its user-friendly interface and does not require any programming skills, making it accessible to many users. Additionally, it offers a number of ready-made scraping recipes and the ability to create custom ones, adding flexibility to its use.

Recommended for

  • Researchers
  • Marketers
  • Data Analysts
  • Business Professionals
  • Anyone needing to automate data extraction from websites

Overall verdict

  • Overall, Streamlit is well-regarded for its ease of use, speed of development, and ability to create clean and professional-looking applications without in-depth web development knowledge. It provides a seamless bridge between complex data analysis and user-friendly presentation, which can be highly beneficial for a wide range of use cases.

Why this product is good

  • Streamlit is a popular choice for quickly building and deploying data applications and interactive dashboards with minimal code. It is designed to be user-friendly, allowing data scientists and engineers to transform their scripts into shareable web apps. It supports real-time updates, is highly customizable, and integrates well with Python libraries like NumPy, Pandas, and Matplotlib, making it an attractive option for many developers working within the Python ecosystem.

Recommended for

    Streamlit is ideal for data scientists, analysts, and developers looking to rapidly prototype and deploy data-driven applications. It is recommended for those who prioritize simplicity, quick deployment, and seamless integration with Python code. Individuals or teams interested in building dashboards, ML model sharing platforms, or interactive reports will find Streamlit particularly useful.

Videos

Walkthroughs and reviews on video.

Data Miner 1 video + Add
Streamlit 3 videos + Add

Data Miner 4.0

My thoughts on web frameworks in Python and R (PyWebIO vs Streamlit vs R Shiny)

More videos

  • - 1/4: What is Streamlit
  • - How to Build a Streamlit App (Beginner level Streamlit tutorial) - Part 1

Category popularity

How often each product is chosen within a category, 0–100% relative to the other.

Score bands 0–20 21–40 41–50 51–60 61–100
Data Miner
Streamlit
100% 100%
0% 0%
0% 0%
100% 100%
100% 100%
0% 0%
0% 0%
100% 100%

User comments

Share your experience with using Data Miner and Streamlit. For example, how are they different and which one is better?

Log in or Post with

Social recommendations and mentions

Recommendations tracked on public social media and blogs since March 2021.

Data Miner 7 mentions
Streamlit 220 mentions

View more

  • How I Bypassed Reddit's Unauthenticated RSS Rate Limits (Without an API Key)
    I wrapped the logic in a small, single-process Streamlit app that pulls the newest posts from Hacker News, Reddit, and Lemmy into one sortable table. A few implementation details worth mentioning:. - Source: dev.to / about 1 month ago
  • Adding Authentication and SSO to a Streamlit App
    Streamlit makes it simple to turn Python scripts into shareable data apps. As these apps move from personal notebooks to team and company use, adding secure authentication and single sign-on (SSO) becomes essential. Authentication... - Source: dev.to / 6 months ago
  • How I trained a computer vision model on the AWS Free Tier
    The app I built to explore that question is a Streamlit app with two modes. Standard mode sends your image to the DetectLabels API and checks if it returns "Egg" or "Easter Egg" in the labels. Custom Labels mode uses a custom model I... - Source: dev.to / 6 months ago

View more

Alternatives to Data Miner and Streamlit

When comparing Data Miner and Streamlit, you can also consider the following products.