SurrealDB Stream #12: Data Modelling and Performance

As SurrealDB is a multi-model database, you have a lot of options for how to model your data. In this stream, we'll take a practical look into different approaches to data modelling and discuss use cases, pros, cons and performance implications.

Featuring:
🗣️ Alexander Fridriksson - Data Evangelist, SurrealDB
🗣️ Micha de Vries - Software Engineer, SurrealDB
🗣️ Tobie Morgan Hitchcock - Co-Founder & CEO, SurrealDB

SurrealDB:
🌍 SurrealDB Twitter: https://surrealdb.com/
👉 SurrealDB GitHub: https://github.com/surrealdb/surrealdb
🐦 SurrealDB Twitter: https://twitter.com/surrealdb
👨‍💻 SurrealDB LinkedIn: https://www.linkedin.com/company/surrealdb/
👉 SurrealDB Discord: https://discord.com/invite/surrealdb
📸 SurrealDB Instagram: https://www.instagram.com/surrealdb
👚 Shop the merch: https://surrealdb.store/

What is SurrealDB?
SurrealDB is an end-to-end cloud-native database designed for modern applications, including web, mobile, serverless, Jamstack, backend, and traditional applications. With SurrealDB, you can simplify your database and API infrastructure, reduce development time, and build secure, performant apps quickly and cost-effectively.

Key features of SurrealDB:
⭐ Reduces development time: SurrealDB simplifies your database and API stack by removing the need for most server-side components, allowing you to build secure, performant apps faster and cheaper.
⭐ Real-time collaborative API backend service: SurrealDB functions as both a database and an API backend service, enabling real-time collaboration.
⭐ Support for multiple querying languages: SurrealDB supports SQL querying from client devices, GraphQL, ACID transactions, WebSocket connections, structured and unstructured data, graph querying, full-text indexing, and geospatial querying.
⭐ Granular access control: SurrealDB provides row-level permissions-based access control, giving you the ability to manage data access with precision.