Surrealdb
SurrealDB is a multi-model database that combines the flexibility of document stores with the relational power of graph databases, enabling developers to model complex data relationships without sacrificing query performance. It supports schemafull and schemaless data, ACID transactions, and a rich query language called SurrealQL that simplifies data manipulation across multiple paradigms. Designed for the realtime web, SurrealDB provides built-in live queries that push real-time updates to connected clients whenever data changes, making it ideal for collaborative applications, dashboards, and interactive experiences. Its distributed architecture allows horizontal scaling across multiple nodes with automatic sharding and replication, ensuring high availability and fault tolerance. SurrealDB can be self-hosted on-premises or in the cloud, with official Docker images and support for Kubernetes. It offers client libraries for various programming languages and integrates with existing tooling, reducing the complexity of building modern, data-intensive applications.
- Category
- Dev Tools
- Pricing
- Open Source
Problem solved
SurrealDB addresses the challenge of building real-time, collaborative applications that require flexible data modeling and horizontal scalability. By unifying document and graph database features with live query subscriptions, it eliminates the need for separate databases, caching layers, and synchronization mechanisms, streamlining development and reducing operational overhead.
Use cases
- Building realtime collaborative applications such as shared documents or whiteboards
- Storing and querying connected data for social networks or recommendation engines
- Powering IoT data pipelines with live dashboards and alerts
- Managing user profiles and permissions in multi-tenant SaaS platforms
- Backend for mobile and web apps requiring offline sync and real-time updates
- Content management systems with flexible schemas and versioning
Audience
- Developers
- Enterprise
- Startups
Pros
- Unified multi-model approach reduces the need for multiple databases
- Real-time live queries enable instant data sync without extra infrastructure
- Built-in distributed clustering with automatic sharding and replication
- Simple and expressive SurrealQL language for complex queries
- ACID compliance ensures data integrity for transactional workloads
Cons
- Relatively newer ecosystem with fewer third-party tools and integrations
- BSL license may restrict use in certain commercial scenarios
- SurrealQL has a learning curve compared to standard SQL
- Limited adoption compared to established databases like PostgreSQL or MongoDB
- Tooling and community resources are still maturing
Official website: https://github.com/surrealdb/surrealdb
Canonical LambdaBase page: https://www.lambdabase.com/tools/surrealdb