In modern application development, managing various database types for different data models is common. This lack of integration can result in complex architectures, increased security risks, and fragmented development processes.
SurrealDB is a Rust-developed open-source, multi-model database that combines features of relational, document, graph, time series, search, and vector databases. It accommodates both schema-less and schema-full data models, utilizing a SQL-like query language.
The project has quickly gained traction, and version 3.0 was recently released, emphasizing AI-powered analysis of unstructured data within the database, and tools for developing event-driven applications.
Tobie Morgan Hitchcock, CEO and co-founder of SurrealDB, discusses with Kevin Ball in a podcast about SurrealDB’s capabilities, multi-model data handling, unstructured data processing, creating event-driven AI applications, and integrating databases with AI models.
*Full Disclosure: This episode is sponsored by SurrealDB.*
Kevin Ball, VP of engineering at Mento and independent engineer coach, co-founded two companies, initiated the San Diego JavaScript meetup, and runs the AI inaction discussion group through Latent Space.
[See the transcript of this episode here.](http://softwareengineeringdaily.com/wp-content/uploads/2025/05/SED1838-SurrealDB.txt)