Intro to SurrealDB
Our vision is to be the ultimate data platform for tomorrow's technology by being the most powerful multi-model AI-native database platform and serverless cloud offering for developers, SMEs and enterprises.
There is a lot to unpack there, and you might have rolled your eyes just now due to the corporate speak, but don't worry. We'll explain what this means in practice through the story of why SurrealDB was created and the problems it solves.
Dreaming of something better
After years of building cloud-based SaaS systems with real-time APIs, complicated security permissions, and multiple separate database backends, our founders Tobie and Jaime were dreaming of something better.
In 2015, those dreams started turning into concepts and plans for a new database platform for building and scaling applications more quickly.
They dreamed of something structured yet flexible, a solution that could handle schemafull data patterns like a relational database, but without the complex JOINs. The database they envisioned was one that could compete with the best document databases for schemaless data patterns, but with a nicer, more powerful query language.
They wanted to build something that lets you build real-time applications effortlessly, a database that requires little to no configuration and can fit on embedded devices yet can scale up and out to distributed clusters of any size.
Finally, they wanted to make a lot of separate backend services optional so that you could build applications directly against the database, putting an end to the following:
Complicated backend integrations with bad API documentation
Learning multiple query languages
Complicated, and often error-prone, security permissions.
In short, a database that allows us to focus on our apps, not our infrastructure.
Turning the dream into reality
Development began in 2016 to create this dream database with inspiration taken from a range of databases, including MySQL, OrientDB, CouchDB, InfluxDB, DynamoDB, MongoDB, RethinkDB, CockroachDB, Neo4j, and Firebase.
The result was SurrealDB, combining the best parts of these database models into one powerful multi-model data platform written in the Rust programming language and importantly, having one unified query language.
We'll cover the specific concepts and architecture details throughout the course, as it's easier to understand and remember in the appropriate context when we're learning hands-on. However if you just want to read it all in one place right now, you can find the specifics in our architecture and concepts docs pages.
We're now closer than ever to turning the dream of something better into reality for the thousands of developers, SMEs and enterprises like you.
Thank you for being on this journey with us and I'll see you in the next one.