Software Alternatives, Accelerators & Startups

Plotly VS HeidiSQL

Compare Plotly VS HeidiSQL and see what are their differences

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Plotly logo Plotly

Low-Code Data Apps

HeidiSQL logo HeidiSQL

HeidiSQL is a powerful and easy client for MySQL, MariaDB, Microsoft SQL Server and PostgreSQL. Open source and entirely free to use.
  • Plotly Landing page
    Landing page //
    2023-07-31
  • HeidiSQL Landing page
    Landing page //
    2021-09-15

Plotly features and specs

  • Interactivity
    Plotly offers highly interactive plots that allow users to pan, zoom, and hover over data points for more information. This enhances the user experience and provides deeper insights.
  • High-quality visualizations
    It provides aesthetically pleasing and highly customizable charts, making it suitable for publication-quality visuals.
  • Versatility
    Plotly supports multiple chart types including line charts, scatter plots, bar charts, and 3D plots, making it suitable for a wide range of applications.
  • Python integration
    Plotly is well-integrated with Python and works seamlessly with other popular data science libraries like Pandas, NumPy, and Scikit-learn.
  • Web-based
    The plots can be easily embedded in web applications or dashboards, making it ideal for sharing insights over the internet.
  • Open-source
    Plotly offers an open-source version, which allows users to create and share visualizations without any cost.

Possible disadvantages of Plotly

  • Performance
    Rendering very large datasets can sometimes be slow, which may not be suitable for real-time data visualization requirements.
  • Learning curve
    Even though the library is well-documented, the extensive range of features can have a steep learning curve for beginners.
  • Cost for advanced features
    While the basic functionality is free, more advanced features, such as export to certain formats and additional customizable options, require a paid subscription.
  • Dependency management
    Plotly has a number of dependencies that need to be managed properly, which can sometimes complicate the setup process.
  • Complexity
    For simple visualizations, Plotly might be overkill and simpler libraries like Matplotlib or Seaborn could be more appropriate.

HeidiSQL features and specs

  • Cost
    HeidiSQL is open-source and free to use, which makes it an affordable choice for individuals and organizations.
  • Multiple Database Support
    The tool supports a wide range of database systems including MySQL, MariaDB, PostgreSQL, and SQL Server, providing flexibility for users.
  • User-Friendly Interface
    HeidiSQL offers an intuitive and easy-to-navigate interface, making it accessible for both beginners and experienced users.
  • Query Editor
    The integrated query editor includes syntax highlighting and autocompletion, which enhances productivity and reduces errors.
  • Data Export and Import
    Users can easily export and import data in various formats like CSV, SQL, and XML, facilitating data management tasks.
  • Active Community
    A strong community of users and developers provides support, plugins, and regular updates.
  • Session Management
    HeidiSQL offers advanced session management features, allowing users to handle multiple database connections simultaneously.

Possible disadvantages of HeidiSQL

  • Platform Limitation
    HeidiSQL is primarily designed for Windows, which can be a limitation for users on other operating systems like macOS and Linux.
  • Lacks Some Features
    Compared to some other database management tools, HeidiSQL may lack advanced features such as graphical execution plans and integrated SSH tunneling.
  • Performance Issues
    Users have reported occasional performance issues, especially when dealing with large datasets or complex queries.
  • Learning Curve
    While generally user-friendly, some features and configurations can still be complex for beginners, necessitating time to learn.
  • Limited Data Visualization
    The tool offers limited data visualization options, which may not be sufficient for users requiring advanced data analytics capabilities.
  • Dependency on Wine for Linux
    Running HeidiSQL on Linux typically requires using Wine, which can introduce compatibility issues and reduce performance.

Analysis of Plotly

Overall verdict

  • Overall, Plotly is a strong choice for those looking to create dynamic and interactive data visualizations, thanks to its range of features and ease of integration with web technologies.

Why this product is good

  • Plotly is considered good because it offers a comprehensive suite of tools for creating interactive visualizations that can be used in web applications, reports, and dashboards. It supports many different types of plots, is easy to use for both beginners and experienced developers, and integrates well with popular programming languages like Python, R, and JavaScript.

Recommended for

    Plotly is recommended for data scientists, analysts, and developers who need to create interactive and visually appealing data visualizations. It's particularly useful for those who work with Python or R and want the ability to embed their visualizations in web applications or dashboards.

Analysis of HeidiSQL

Overall verdict

  • HeidiSQL is generally considered a good SQL client, especially for users who work with MySQL, MariaDB, and PostgreSQL databases.

Why this product is good

  • User-Friendly Interface: HeidiSQL offers an intuitive and clean interface suitable for both beginners and experienced database administrators.
  • Feature-Rich: It provides a range of features such as database management, data browsing and editing, session management, query execution, and export/import capabilities.
  • Performance: HeidiSQL is lightweight, fast, and responsive, making it an efficient tool for database management.
  • Community Support: Being an open-source tool, it has a strong community that contributes to its development and offers support via forums and other channels.
  • Cross-Platform Compatibility: Though originally designed for Windows, HeidiSQL can be used on Unix-based systems using Wine, allowing for wider accessibility.

Recommended for

  • Database Administrators: Those who need a reliable and straightforward tool for managing MySQL, MariaDB, and PostgreSQL databases.
  • Developers: Coders who require an effective way to interact with their databases during the development process.
  • Students: Individuals learning SQL and database management who need a tool to practice and apply their knowledge.
  • Freelancers: Independent professionals who need a free, yet powerful, tool for their database tasks.

Plotly videos

Create Real-time Chart with Javascript | Plotly.js Tutorial

More videos:

  • Review - Introducing plotly.py 3.0
  • Review - Is Plotly The Better Matplotlib?
  • Tutorial - Plotly Tutorial 2021
  • Review - Data Visualization as The First and Last Mile of Data Science Plotly Express and Dash | SciPy 2021

HeidiSQL videos

[HeidiSQL] Main features review

More videos:

  • Review - Tutorial HeidiSQL with MariaDB and MySQL Part 5 Relation 2 tables and more
  • Tutorial - HeidiSQL Tutorial 05 :- How to Import and Export database in HeidiSQL

Category Popularity

0-100% (relative to Plotly and HeidiSQL)
Data Visualization
100 100%
0% 0
Databases
0 0%
100% 100
Data Dashboard
100 100%
0% 0
Database Management
0 0%
100% 100

User comments

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Reviews

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

Plotly Reviews

Best 8 Redash Alternatives in 2023 [In Depth Guide]
Plotly is specifically designed for companies who want to build and deploy analytic applications like dashboards using Python, Julia, or R without needing DevOps or Javascript developers.
Source: www.datapad.io
5 Best Python Libraries For Data Visualization in 2023
Plotly is a web-based data visualization toolkit that comes with unique functionalities such as dendrograms, 3D charts, and also contour plots, which is not very common in other libraries. It has a great API offering scatter plots, line charts, bar charts, error bars, box plots, and other visualizations. Plotly can even be accessed from a Python Notebook.
Top 8 Python Libraries for Data Visualization
Plotly is a free open-source graphing library that can be used to form data visualizations. Plotly (plotly.py) is built on top of the Plotly JavaScript library (plotly.js) and can be used to create web-based data visualizations that can be displayed in Jupyter notebooks or web applications using Dash or saved as individual HTML files. Plotly provides more than 40 unique...
5 top picks for JavaScript chart libraries
Plotly is a graphing library that’s available for various runtime environments, including the browser. It supports many kinds of charts and graphs that we can configure with a variety of options.

HeidiSQL Reviews

  1. Mark-Mercer
    · self emloyed dba at Shatz ·
    very good and handy tool

    There was a need to work with the MS SQL database, but I did not want to install and understand the complex SQL Management Studio program, and this product turned out to be very easy to install and use. For more then 2 month i've used the tool haven't came across any issues.

    🏁 Competitors: SQL Server Management Studio
    👍 Pros:    Lightweight|Simple yet powerful and efficient tool|Many built-in features
    👎 Cons:    Nothing, so far

TOP 10 IDEs for SQL Database Management & Administration [2024]
HeidiSQL is one of the most popular multidatabase IDEs for database developers and administrators. It is free and open-source, thus opening excellent customization possibilities for the users. Also, it offers decent functionality to perform standard tasks across diverse databases. Though it lacks some advanced options that might be found in more robust IDEs, HeidiSQL can...
Source: blog.devart.com
5 Free & Open Source DBeaver Alternatives for 2024
Created in 2002, HeidiSQL is a well respected and mature GUI for managing MySQL, MariaDB, Microsoft SQL, and PostgreSQL databases on Microsoft Windows. It offers a robust set of features including a graphical interface for managing databases and data visually.
Top Ten MySQL GUI Tools
Navicat for MySQL is a powerful graphical interface that synchronizes your connection settings, models, and queries to the Navicat Cloud for automatic saving and sharing at any given time. Just like HeidiSQL, Navicat for MySQL has the ability to connect to a MySQL database through an SSH tunnel. It also offers workable data migration by providing comprehensive data format...
Top 10 of Most Helpful MySQL GUI Tools
The existing database tools for MySQL are many, and you can always find the right solution. There are both free and paid solutions. While the freeware tools like HeidiSQL or the Workbench free edition provide the basic functionality to do quintessential jobs, database professionals often need additional options. In this aspect, we’d recommend turning to advanced toolsets...
Source: www.hforge.org
20 Best SQL Management Tools in 2020
HeidiSQL is another reliable SQL management tool. It is designed using the popular MySQL server, Microsoft SQL databases, and PostgreSQL. It allows users to browse and edit data, create and edit tables, views, triggers and scheduled events.
Source: www.guru99.com

Social recommendations and mentions

Based on our record, Plotly seems to be more popular. It has been mentiond 33 times since March 2021. 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.

Plotly mentions (33)

  • Python for Data Visualization: Best Tools and Practices
    Plotly is perfect for interactive visualizations. You can create interactive charts and graphs that allow users to hover, click, and zoom in. Plotly is also great for web-based visuals, making it easy to share your findings online. - Source: dev.to / 2 months ago
  • Generative AI Powered QnA & Visualization Chatbot
    Front End: A React application that leverages React-Chatbotify library to easily integrate a chatbot GUI. It also uses the Plotly library to display the charts/visualizations. The generative AI implementation and details are entirely abstracted from the front end. The front-end application depends on a single REST endpoint of the backend application. - Source: dev.to / 4 months ago
  • Build a Stock Dashboard in less than 40 lines of Python code!🤓
    In this tutorial, Mariya Sha will guide you through building a stock value dashboard using Taipy, Plotly, and a dataset from Kaggle. - Source: dev.to / 6 months ago
  • Essential Deep Learning Checklist: Best Practices Unveiled
    How to Accomplish: Utilize visualization libraries like Matplotlib, Seaborn, or Plotly in Python to create histograms, scatter plots, and bar charts. For image data, use tools that visualize images alongside their labels to check for labeling accuracy. For structured data, correlation matrices and pair plots can be highly informative. - Source: dev.to / 12 months ago
  • Python equivalent to power bi/power query?
    For dashboards: - https://plotly.com/ is probably my favourite, but there are others like streamlit, voila and others... Source: over 1 year ago
View more

HeidiSQL mentions (0)

We have not tracked any mentions of HeidiSQL yet. Tracking of HeidiSQL recommendations started around Mar 2021.

What are some alternatives?

When comparing Plotly and HeidiSQL, you can also consider the following products

D3.js - D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.

DBeaver - DBeaver - Universal Database Manager and SQL Client.

Chart.js - Easy, object oriented client side graphs for designers and developers.

MySQL Workbench - MySQL Workbench is a unified visual tool for database architects, developers, and DBAs.

RAWGraphs - RAWGraphs is an open source app built with the goal of making the visualization of complex data...

DataGrip - Tool for SQL and databases