PostgreSQL
- Databases
Connect Yurbi to your PostgreSQL databases for real-time data access, empowering you to create detailed reports and engaging dashboards with ease.
About
PostgreSQL is a highly capable open-source relational database management system that stands out for its extensibility and adherence to industry standards. It supports a diverse array of data types and provides powerful features like advanced querying, full-text search, and strong data integrity. Whether for small-scale applications or large enterprise systems, PostgreSQL is a preferred choice for developers and data professionals alike. When integrated with Yurbi, users can access PostgreSQL data in real-time, enabling the creation of detailed reports and dynamic dashboards that support informed decision-making.
Supported Versions
- 9 and above
Integration Capabilities
- Live query read-only access to your data source
- Support for table owner/schema
- Compatibility with Views
- Dynamic Data Source Connection Strings
Requirements
- PostgreSQL User ID with read-only access
- Network/Firewall access to the database instance
Support
Integration FAQs
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How do I get started with this integration?
If you have admin privileges, navigate to Settings > Integration and select Create a New App for the data source you want to use.
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What types of data can I access through this integration?
Yurbi generates SQL queries dynamically using the official database driver, ODBC driver, or API endpoint. Through this integration, you can access a variety of structured data from your data source, such as tables, views, and results from stored procedures in MSSQL and MySQL.
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How do I refresh the data in Yurbi after making changes in my database?
Yurbi performs live queries against your data source, ensuring that every time a report or dashboard is executed, it retrieves the most up-to-date data available. This means you always have access to the latest information without needing to manually refresh anything.
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Can Yurbi cause any damage or harm to my data source?
Yurbi performs read-only queries against the connected data source, meaning it cannot write or modify any data. However, if queries are designed to pull excessive amounts of data, they can consume significant resources, potentially leading to timeouts or increased load that may affect overall performance.