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SurrealDB is a versatile, scalable, and distributed database designed for modern applications, combining document, graph, and key-value models with powerful real-time capabilities.
SurrealDB is a cloud-native, distributed, multi-model database that is specifically built for the realtime web. It offers a powerful and flexible data model, advanced querying, and live data synchronization, simplifying the development of complex, collaborative applications.
Modern web and application development often requires managing complex, interconnected data, enabling real-time collaboration, and ensuring horizontal scalability. Traditional databases typically specialize in only one area, forcing developers to combine multiple technologies. SurrealDB provides a unified solution addressing these challenges.
Combine flexible document storage with powerful graph traversal capabilities within a single database.
Enable instant data synchronisation across all connected clients through live queries and subscriptions.
Easily scale horizontally across multiple nodes to handle high loads and large datasets.
Perform complex ACID transactions across multiple tables and documents.
SurrealDB is well-suited for a wide range of applications that benefit from real-time updates, flexible data modeling, and distributed scalability.
Develop collaborative editors, project management tools, or shared workspaces where multiple users interact with the same data simultaneously and see updates instantly.
Provides built-in real-time features, simplifying complex state synchronization logic on the client and server.
Power online games, social networks, or messaging platforms requiring low-latency data access, complex relationship queries (friends, groups, connections), and handling millions of concurrent users.
Offers high performance, graph capabilities for relationship modeling, and horizontal scalability to accommodate user growth.
Collect, store, and analyze streaming data from IoT devices, allowing for real-time monitoring, dashboards, and complex event processing on time-series and graph data.
Handles high-throughput data ingestion and provides flexible querying and real-time insights from connected devices.
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