17 Best Open Source Data Visualization Tools in 2023

In data-driven decision-making, transforming raw data into meaningful insights is paramount. Open Source Data Visualization Tools have become indispensable assets for organizations and individuals alike, enabling them to harness the power of data through compelling visual representations. In this comprehensive guide, we’ll explore the world of open source data visualization tools, understand their significance, and introduce you to the top 17 options available. We’ll also provide insights on how to choose the best tool for your specific needs and wrap up with a conclusion.

Table of Contents

What Is Data Visualization?

Before diving into the tools, let’s first grasp the concept of data visualization. Data visualization graphically represents data to discover patterns, trends, and insights that might remain hidden in a sea of numbers. It leverages the power of visual elements like charts, graphs, maps, and dashboards to communicate complex information clearly and effectively.

What Are Open Source Data Visualization Tools?

Open Source Data Visualization Tools are software applications or platforms that facilitate the creation of data visualizations while adhering to open-source principles. These tools empower users to transform raw data into visually appealing charts, graphs, and dashboards, allowing for better data-driven decision-making. They are known for their flexibility, cost-effectiveness, and community-driven development.

17 Best Open Source Data Visualization Tools

#1 Apache Superset
#2 Tableau Public (with a limited free version)
#3 D3.js
#4 Plotly
#5 Grafana
#6 Metabase
#7 Chart.js
#8 RawGraphs
#9 Datawrapper
#10 BIRT (Business Intelligence and Reporting Tools)
#11 Redash
#12 Flourish
#13 Keen IO (discontinued but open source)
#14 Power BI Desktop (with a limited free version)
#15 Google Data Studio
#16 VEGA-Lite
#17 QlikView (with a limited free version)

Now, let’s journey through open source data visualization tools. We’ll delve into each tool’s unique features, advantages, and potential limitations to help you make informed choices.

#1. Apache Superset

Apache Superset is an open-source data exploration and visualization platform that simplifies data analysis. It offers a user-friendly interface to create interactive dashboards and share insights.

Features:

• Drag-and-drop dashboard builder
• Support for various data sources
• Rich set of visualization options
• SQL querying and data exploration

Pros:

• Intuitive and accessible for non-technical users
• Quick setup and easy data exploration
• Suitable for creating interactive reports and dashboards

Cons:

• It may lack some advanced analytics features.
• Limited scalability for very large datasets

#2. Tableau Public (with a limited free version)

Tableau Public is a powerful data visualization tool that allows users to create and share interactive charts and dashboards. While it offers a free version, it has limitations on data privacy.

Features:

• User-friendly drag-and-drop interface
• Extensive library of visualization types
• Data sharing and collaboration options
• Support for connecting to various data sources

Pros:

• Intuitive and easy to use for creating stunning visuals
• Active Tableau Public Community
• Suitable for data storytelling and sharing

Cons:

• Limited data privacy and security in the free version
• It may require a paid version for advanced features.

#3. D3.js

D3.js (Data-Driven Documents) is an open-source JavaScript library for creating dynamic and interactive data visualizations in web browsers.

Features:

• Dynamic and interactive data visualizations
• Support for various chart types and customizability
• Strong community and ample online resources
• Data binding to DOM elements

Pros:

• Exceptional for web-based data visualization projects
• Highly customizable and versatile
• Active development and community support

Cons:

• Requires JavaScript and web development skills
• The learning curve for those new to web-based data visualization

#4. Plotly

Plotly is an open-source JavaScript graphing library that simplifies the creation of interactive, publication-quality graphs and dashboards.

Features:

• Rich library of chart types and styling options
• Interactive data visualizations with hover and zoom capabilities
• Support for Python, R, and JavaScript
• Online chart sharing and collaboration

Pros:

• Easy-to-use interface for creating interactive charts
• Suitable for both data exploration and presentation
• Active community and regular updates

Cons:

• Advanced features may require a paid subscription
• The steeper learning curve for complex visuals

#5. Grafana

Grafana is an open-source platform for monitoring and observability, but it’s also a powerful tool for data visualization and analytics. It integrates with various data sources to create dashboards and charts.

Features:

• Support for multiple data sources, including time series databases
• Interactive and real-time dashboard creation
• Alerts and notifications for data anomalies
• Extensible with plugins and integrations

Pros:

• Ideal for real-time data monitoring and visualization
• User-friendly dashboard creation with a drag-and-drop interface
• A wide range of data source plugins are available.

Cons:

• Focused primarily on monitoring, which may limit advanced analytics
• Less suitable for data processing and transformation

#6. Metabase

Metabase is an open-source business intelligence and data visualization tool that empowers users to create interactive dashboards, charts, and reports.

Features:

• Simple and user-friendly dashboard creation
• SQL querying and data exploration
• Integration with various data sources
• Collaboration and sharing features

Pros:

• Intuitive and accessible for non-technical users
• Quick setup and easy data exploration
• Suitable for creating interactive reports and dashboards

Cons:

• It may lack some advanced analytics features.
• Limited scalability for very large datasets

#7. Chart.js

Chart.js is an open-source JavaScript library for creating simple yet visually appealing charts on web pages. It’s particularly suited for small to medium-sized projects.

Features:

• Support for common chart types (e.g., bar, line, pie)
• Lightweight and easy to integrate into web applications
• Responsive and mobile-friendly charts
• Customizable styling options

Pros:

• Ideal for quick and straightforward chart creation
• Lightweight and minimal setup required
• Suitable for adding charts to web applications

Cons:

• Limited in terms of complex chart types and interactivity
• It may not be suitable for large-scale data visualization.

#8. RawGraphs

RawGraphs is an open-source data visualization framework that focuses on creating custom and unique visualizations from raw data.

Features:

• Customizable data visualization templates
• Support for various data import formats
• Interactive and shareable visualizations
• User-friendly drag-and-drop interface

Pros:

• Enables the creation of unconventional and artistic data visualizations
• Suitable for storytelling and custom chart design
• Active development and community support

Cons:

• Less suitable for standard or traditional chart types
• It may require some data preprocessing.

#9. Datawrapper

Datawrapper is an open-source data visualization tool that simplifies the creation of charts and maps for online publications and reports.

Features:

• Easy-to-use chart and map creation interface
• Responsive and mobile-friendly visuals
• Data import from various sources
• Collaboration and sharing features

Pros:

• Quick and hassle-free chart creation
• Suitable for embedding in websites and articles
• User-friendly for non-technical users

Cons:

• Limited in terms of advanced chart customization
• It may require manual data formatting.

#10. BIRT (Business Intelligence and Reporting Tools)

BIRT is an open-source business intelligence and reporting platform with data visualization capabilities. It’s suitable for creating reports, charts, and dashboards.

Features:

• Visual report and dashboard design
• Data integration from multiple sources
• Support for data analysis and scripting
• Extensible with plugins

Pros:

• Tailored for business intelligence and reporting
• Robust data visualization and analysis capabilities
• Active BIRT community and plugin ecosystem

Cons:

• The learning curve for advanced features
• It may be overkill for simple data visualization tasks.

#11. Redash

Redash is an open-source data visualization and exploration platform designed for querying, visualizing, and sharing data from various sources.

Features:

• SQL query and visualization builder
• Integration with multiple data sources
• Collaboration and sharing of queries and dashboards
• Customizable and extensible

Pros:

• User-friendly query and visualization creation
• Suitable for data exploration and sharing insights
• Active development and community support

Cons:

• It may require SQL knowledge for advanced use cases.
• Limited data processing and transformation capabilities

#12. Flourish

Flourish is an open-source data visualization and storytelling platform that simplifies the creation of data-driven narratives, charts, and interactive graphics.

Features:

• User-friendly interface for data storytelling
• Interactive chart templates
• Data import from various sources
• Collaboration and sharing features

Pros:

• Ideal for creating data-driven stories and narratives
• Minimal design and coding skills required
• Suitable for embedding in articles and websites

Cons:

• Limited in terms of advanced data analysis
• It may not cover all chart types and customization options.

#13. Keen IO (discontinued but open source)

Keen IO, while discontinued, remains an open-source platform for event data collection, analysis, and visualization. It’s suitable for real-time data analysis.

Features:

• Real-time event data collection
• Data analysis and querying capabilities
• Customizable data dashboards
• Integration with various data sources

Pros:

• Ideal for real-time data analytics and visualization
• Customizable and extensible for specific use cases
• Active community support despite discontinuation

Cons:

• Limited to event data analytics
• It may require self-hosting and maintenance due to discontinuation.

#14. Power BI Desktop (with a limited free version)

Power BI Desktop is a Microsoft product that offers a free version with some limitations. It’s a robust tool for creating interactive reports and dashboards.

Features:

• Visual report and dashboard design
• Data integration from various sources
• Advanced data modeling and DAX (Data Analysis Expressions) language
• Integration with the Power BI service

Pros:

• A comprehensive tool for business intelligence and data visualization
• Strong integration with Microsoft products and services
• Active Power BI community and ecosystem

Cons:

• Limited data refresh and sharing capabilities in the free version.
• It may require a paid subscription for full functionality.

#15. Google Data Studio

Google Data Studio is an open-source data visualization tool that simplifies the creation of interactive dashboards and reports using Google’s ecosystem.

Features:

• Drag-and-drop dashboard builder
• Data integration from Google services and other sources
• Collaboration and sharing of reports
• Real-time data updates

Pros:

• Seamless integration with Google products
• User-friendly dashboard creation with a familiar interface
• Suitable for creating interactive and real-time reports

Cons:

• Limited in terms of data sources compared to other tools
• It may require manual data preprocessing.

#16. VEGA-Lite

VEGA-Lite is an open-source high-level visualization grammar for creating expressive, concise, and interactive data visualizations.

Features:

• Declarative specification of visualizations
• Support for various chart types and data formats
• Interactive and dynamic visuals
• Extensible and customizable

Pros:

• Enables the creation of complex visualizations with concise code
• Suitable for embedding in web applications
• Active development and growing community

Cons:

• Requires some knowledge of JSON and data specifications
• It may not cover all advanced chart types.

#17. QlikView (with a limited free version)

QlikView is a data visualization and business intelligence platform with a limited free version. It’s suitable for creating interactive dashboards and reports.

Features:

• Drag-and-drop dashboard builder
• Associative data model for rapid analysis
• Data integration from multiple sources
• Collaboration and sharing of insights

Pros:

• Powerful associative data model for dynamic analysis
• Suitable for business intelligence and data exploration
• Active QlikView community and resources

Cons:

• Limited data reload and sharing options in the free version
• It may require a paid license for advanced features.

These 17 open source data visualization tools offer diverse capabilities, from creating simple charts to designing complex dashboards and interactive reports. As you consider which tool aligns with your specific requirements, you must evaluate factors such as the type of data you’re working with, the complexity of your visualization needs, and the level of technical expertise available in your team.

How to Choose the Best Data Visualization Tool?

Selecting the ideal open-source data visualization tool for your projects involves careful consideration of various factors:

• Data Complexity: Assess the complexity of your data. Some tools are better suited for simple charts, while others excel in handling complex, multidimensional data.
• Data Sources: Consider the sources of your data. Ensure the tool can connect to and integrate data from your chosen sources, whether databases, spreadsheets, or cloud services.
• Interactivity: Determine the level of interactivity you require in your visualizations. Some tools offer advanced interactive features, while others are more suitable for static charts and reports.
• Skillset: Evaluate the technical skills of your team. Choose a tool that matches the expertise of your users, whether they are data analysts, business users, or developers.
• Budget: Keep in mind any budget constraints. While many open-source tools are free, some may offer premium features in paid versions.
• Scalability: Consider the scalability of the tool. Ensure it can handle your data volume and growth over time.
• Community and Support: Look for tools with active user communities and regular updates, as this can provide valuable support and ensure the tool’s longevity.

Conclusion

Open Source Data Visualization Tools are your gateway to transforming data into actionable insights. From interactive dashboards to eye-catching charts, these tools empower individuals and organizations to make informed decisions based on data-driven narratives. By exploring the features, advantages, and limitations of the top 17 open source data visualization tools and understanding your specific project needs, you can embark on a data visualization journey that unlocks the full potential of your data.