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DjangoCon 2022 | Why would anyone use Snowflake as a backend for Django?
Discover why Snowflake is a great choice as a backend for Django, and learn how it can help you build scalable and performant data apps, with its ability to handle big data, support for multiple workloads, and corporate sponsorship for innovation.
- Snowflake can be used as a backend for Django due to its ability to scale and handle big data.
- Snowflake runs Python code, allowing for UDFs and logic to be moved inside the data warehouse.
- Corporate sponsorship for Snowflake development can bring innovative solutions to the open-source community.
- Django and Snowflake can be combined to build data apps, and it’s a good choice for big data projects.
- Snowflake’s architecture allows for data analytics and OLAP, making it suitable for transactional and analytical use cases.
- The Snowflake database is built for the cloud and has infinite storage capacity.
- Snowflake supports multiple workloads, including data engineering, data lake, data warehouse, data science, and data sharing.
- The combination of Django and Snowflake can handle big data and provide a scalable solution.
- Snowflake’s transactional workload allows for indexes, constraints, and faster query performance.
- Corporate sponsorship is essential for open-source development and innovation.
- The Snowflake community is essential for building data apps and facilitating data sharing.
- The combination of Django and Snowflake can provide a scalable and performant solution for big data projects.
- Snowflake’s architecture makes it suitable for transactional and analytical use cases.
- The company behind Snowflake is dedicated to open-source development and wants to work with the Python community.
- The combination of Django and Snowflake can provide a flexible and powerful solution for data apps.