

PyQueryHub
PyQueryHub is a comprehensive data analytics platform that connects to multiple databases, enables SQL querying with dynamic parameters, creates interactive visualizations and reports and supports Python notebooks for analysis and many more features.
Cost / License
- Freemium (Subscription)
- Proprietary
Application type
Platforms
- Online
Features
Properties
- Privacy focused
- Lightweight
Features
- Real time collaboration
- Ad-free
- AI-Powered
- Data visualization
- Data analytics
PyQueryHub News & Activities
Recent activities
- pyqueryhub added PyQueryHub
pyqueryhub added PyQueryHub as alternative to Tableau, Microsoft Power BI, Redash and Zoho Analytics
PyQueryHub information
What is PyQueryHub?
PyQueryHub - All-in-One Data Analytics and Reporting Platform PyQueryHub is a powerful, collaborative data analytics platform designed to streamline the entire workflow from database connection to report sharing. It eliminates the need for multiple disconnected tools by providing a unified environment for querying, visualizing, and distributing data insights. Key Features: Universal Database Connectivity Connect securely to a wide range of data sources including MySQL, PostgreSQL, BigQuery, Google Sheets, and more. Supports SSH tunneling and SSL encryption for secure connections with comprehensive credential management. Interactive SQL Query Interface Write and execute SQL queries in an intuitive editor with real-time result viewing. Inspect rendered SQL and manage query versions efficiently. Dynamic Parameters with Liquid Templating Define interactive parameters using YAML configuration, making reports dynamic and reusable. Use Liquid templating to inject parameters directly into queries for flexible data exploration. Rich Visualization Options Transform query results into compelling visualizations with multiple chart types, pivot tables, and data grids. Drag-and-drop interface for easy configuration and field customization. Embedded Python Notebooks Integrate Jupyter-style Python notebooks directly into your workflow. Perform advanced analysis with pandas, create custom visualizations with Matplotlib, and add notebook outputs directly to reports. Flexible Report Builder Assemble comprehensive reports by combining charts, tables, and notebook outputs. Intuitive edit mode with customizable layouts, element sizing, and arrangement options. Automated Scheduling Schedule query and report executions to keep data fresh and stakeholders informed automatically. Set custom intervals for data updates. Smart Alerts and Monitoring Monitor key metrics and receive notifications when specific conditions are met. Define alert rules based on query results with configurable cooldown periods to manage notification frequency. Secure Embedding Capabilities Embed reports into external applications using a robust two-token security system. Generate long-lived Personal API Tokens and short-lived Report Access Tokens for secure iframe embedding in your own applications. Perfect For:
Data analysts building interactive dashboards Development teams embedding analytics into applications Business intelligence professionals creating scheduled reports Data scientists combining SQL with Python analysis Organizations needing secure, shareable data insights
PyQueryHub bridges the gap between data exploration and distribution, making it easier for teams to collaborate on data-driven decisions without switching between multiple tools.








