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DataGrip VS Streamlit

Compare DataGrip VS Streamlit and see what are their differences

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Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

DataGrip logo DataGrip

Tool for SQL and databases

Streamlit logo Streamlit

Turn python scripts into beautiful ML tools
  • DataGrip Landing page
    Landing page //
    2023-03-16
  • Streamlit Landing page
    Landing page //
    2023-10-07

DataGrip features and specs

  • Cross-Platform Support
    DataGrip runs on multiple operating systems including Windows, macOS, and Linux, providing flexibility across various development environments.
  • Intelligent Query Console
    The query console offers code completion, syntax highlighting, and on-the-fly error detection, making SQL coding faster and more accurate.
  • Database Support
    Supports a wide range of databases, including MySQL, PostgreSQL, SQLite, Oracle, and many others, allowing users to manage different database systems within one tool.
  • Data Visualization
    Provides powerful data visualization tools, including table and schema views, which help in understanding and managing the data more effectively.
  • Refactoring Tools
    Includes advanced refactoring capabilities such as renaming, changing column types, and finding usages, which help maintain and update databases with ease.
  • Version Control Systems Integration
    Integrates with popular VCS systems like Git and SVN, allowing for seamless code versioning and collaboration.
  • Customizable Interface
    Highly customizable interface with various themes and layout configurations that adapt to different working styles and preferences.

Possible disadvantages of DataGrip

  • Cost
    DataGrip is a commercial tool and requires a subscription, which may be a significant cost for individual developers or small teams.
  • Resource Intensive
    Tends to consume a considerable amount of system resources, which may affect performance on less powerful machines.
  • Steep Learning Curve
    The tool offers a wide range of features and customizations that can be overwhelming for beginners and may require time to learn and master.
  • Occasional Bugs
    Users have reported occasional bugs and instability issues, which can disrupt workflow and productivity.
  • Limited Non-SQL Database Support
    Primarily designed for SQL databases and has limited support or features for non-SQL databases compared to specialized tools.
  • Complex Configuration
    Initial setup and configuration can be complex, particularly when integrating with various databases and external tools.

Streamlit features and specs

  • 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 of Streamlit

  • 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 of Streamlit

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.

DataGrip videos

+ Add

DataGrip Introduction

Streamlit videos

+ Add

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

More videos:

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

Category Popularity

0-100% (relative to DataGrip and Streamlit)

DataGrip

Streamlit

Database Management
100 100%
Database Management
0% 0
Developer Tools
0 0%
Developer Tools
100% 100
Databases
100 100%
Databases
0% 0
Productivity
0 0%
Productivity
100% 100

User comments

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

These are some of the external sources and on-site user reviews we've used to compare DataGrip and Streamlit

DataGrip Reviews

Best SQL Manager Tools for Database Development in 2026
DataGrip is JetBrainsโ€™ database IDE specifically designed for SQL development. The focus is on the query editing experience, with smart code completion, refactoring tools, and live SQL analysis. The tool works with many database platforms and integrates into JetBrainsโ€™ broader developer ecosystem. While DataGrip is a powerful tool for writing and exploring queries, it is...
Source: www.tycoonstory.com
Top 8 PostgreSQL GUI Tools with AI for 2026
Itโ€™s not PostgreSQL-specific, but thatโ€™s the point. DataGrip fits environments where teams switch between databases and need one consistent interface. AI features come through JetBrains AI, helping generate and explain queries, though theyโ€™re not as deeply integrated into PostgreSQL workflows as dedicated tools.
Source: dbajamey.github.io
Bestย Oracle Database Tools for Developers and DBAsย [Free & Paid]
This software is popular for its highly customizable interface with multiple UI skins, enabling users to tailor the looks to their preferences, hide unnecessary elements, and arrange features and options for easy access. DataGrip also offers intelligent PL/SQL coding assistance, code editing and debugging tools, visual database design capabilities, database connection...
Source: blog.devart.com
Best GUI Client for SQL Databases
DataGrip is listed among the most easy-to-customize SQL GUI tools for a reason โ€” it comes with a window layout you can tweak to match your needs, window float and auto-hide options, syntax highlighting that you can customize, and UI skins you can choose from. Moreover, if you want a tool to edit objects and data, work with database design, and perform SQL editing, it will...
Source: blog.devart.com
Top 7 MySQL Clients for Mac OS X
Datagrip is an advanced database client developed by JetBrains released in 2016. It's designed for developers who need to manage multiple database types for their projects. Datagrip provides a wide range of powerful features.
Source: blog.bartzz.com

Streamlit Reviews

We have no reviews of Streamlit yet.
Be the first one to post

Social recommendations and mentions

Based on our record, Streamlit seems to be a lot more popular than DataGrip. While we know about 219 links to Streamlit, we've tracked only 1 mention of DataGrip. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

DataGrip mentions (1)

  • Which Is The Best PostgreSQL GUI? 2021 Comparison
    DataGrip is a cross-platform integrated development environment (IDE) that supports multiple database environments. The most important thing to note about DataGrip is that it's developed by JetBrains, one of the leading brands for developing IDEs. If you have ever used PhpStorm, IntelliJ IDEA, PyCharm, WebStorm, you won't need an introduction on how good JetBrains IDEs are. - Source: dev.to / over 5 years ago

Streamlit mentions (219)

  • 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 protects sensitive data and gates features by user identity. SSO lets people sign in once and move across apps without repeating logins. - Source: dev.to / 4 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 trained on my own images. Both draw bounding boxes around any eggs they find. - Source: dev.to / 4 months ago
  • How to Analyze 47 Million Hacker News Posts: A Data Scientist's Dream Dataset Just Got Better
    Once you've completed your analysis, consider building a dashboard to visualize your findings. Tools like Streamlit make it easy to create interactive web apps:. - Source: dev.to / 4 months ago
  • [TIL][Python] Python Tool for Online PDF Viewing, Comparison, and Data Import
    Title: [TIL][Python] Online PDF Page-by-Page Viewing and Comparison Tool for Importing Data (Python online PDF Viewer and comparison) and Python Snippets Published: false Date: 2023-08-04 00:00:00 UTC Tags: Canonical_url: http://www.evanlin.com/til-python-tips/ --- ## Small Project: Online PDF Viewer and Parse Data compare: -... - Source: dev.to / almost 3 years ago
  • Experimenting with Javelit - The Streamlit for Java
    Javelit brings the power of rapid prototyping and interactive web app development to the Java ecosystem, much like Streamlit does for Python. With its simple, loop-based programming model, developers can quickly build data-driven applications without needing extensive frontend knowledge, leveraging familiar Java syntax and the rich JVM ecosystem. The live-reload feature enables instant experimentation and... - Source: dev.to / 7 months ago
View more

What are some alternatives?

When comparing DataGrip and Streamlit, you can also consider the following products

DBeaver - DBeaver - Universal Database Manager and SQL Client.

Anvil.works - Build seriously powerful web apps with all the flexibility of Python. No web development experience required.

HeidiSQL - HeidiSQL is a powerful and easy client for MySQL, MariaDB, Microsoft SQL Server and PostgreSQL. Open source and entirely free to use.

FastAPI - FastAPI is an Open Source, modern, fast (high-performance), web framework for building APIs with Python 3.6+ based on standard Python type hints.

Navicat - Powerful database management & design tool for Win, Mac & Linux. With intuitive GUI, user manages MySQL, MariaDB, SQL Server, SQLite, Oracle & PostgreSQL DB easily.

Gradio - Build & share machine learning apps delightfully.

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