SurrealDB

SurrealDB is an end-to-end cloud-native database explicitly engineered for modern application development, spanning web, mobile, serverless, and traditional systems. It tackles the common pain point of infrastructure sprawl by unifying the database, API layer, and security permissions into a single, performant service. By consolidating these components, SurrealDB significantly reduces development time, complexity, and costs, allowing you to build highly secure, real-time applications quickly and efficiently.

Key Features

SurrealDB is designed to offer unparalleled flexibility and power, integrating functionalities that traditionally require an entire suite of separate services.

• ⚡ Unified Multi-Model Architecture SurrealDB natively supports multiple data paradigms—including document, relational, and graph—within a single, fully ACID-compliant system. This allows you to model complex relationships using record links and directed graph connections, while still leveraging standard tables and unstructured documents, eliminating the need to manage specialized databases for different data types.

• 🌐 Real-Time API Backend Service The database functions as its own API backend, supporting direct connections from client devices (web browsers, mobile apps) via WebSockets and HTTP. This capability enables Live Queries, which automatically push data changes to subscribed clients, delivering true real-time synchronization and collaboration without requiring you to build custom server-side middleware or routing logic.

• 🔒 Granular Row-Level Security Implement highly precise security permissions directly within the database schema. SurrealDB offers row-level permissions, customizable authentication scopes, and multi-tenancy data separation using namespaces. This ensures that even when clients connect directly, you maintain complete, fine-grained control over who can select, create, update, or delete specific records.

• 🧠 Embedded Machine Learning (SurrealML) Integrate custom machine learning models (trained using PyTorch, TensorFlow, or Sklearn) directly into the database for native, high-performance inference. Models are imported and run by a Rust-native runtime, allowing you to execute predictions or data analysis alongside your data using SurrealQL, complete with automatic input mapping and normalization.

• 📐 Comprehensive Querying & Indexing SurrealDB’s powerful querying language, SurrealQL, supports traditional SQL statements alongside advanced capabilities like graph traversal, full-text indexing with configurable analyzers, geospatial querying (GeoJSON support), and efficient vector embedding indexing (using Euclidean distance) for similarity matching and advanced data analysis.

Use Cases

SurrealDB’s unique combination of features makes it ideal for several demanding modern use cases:

1. Developing Highly Collaborative Applications: Utilize Live Queries and WebSocket connectivity to power collaborative productivity tools (like shared whiteboards or multi-user document editors) or sophisticated monitoring dashboards. Since the data updates are handled natively by the database, you drastically reduce latency and the complexity associated with synchronizing state across numerous simultaneous users.

2. Simplifying and Securing Full-Stack Deployment: By acting as the end-to-end API backend, SurrealDB allows you to connect frontends (using available SDKs for React, Vue, Angular, etc.) directly to the database. This eliminates the need to maintain and scale a separate application server layer for standard CRUD operations and authentication, resulting in a cleaner, faster deployment pipeline and reduced operational overhead.

3. Advanced Data Analysis and Decision Support: Leverage the multi-model and embedded analytics capabilities to derive insights instantly. For example, combine customer purchase records (relational data) with their social network structure (graph data) and use SurrealML to run real-time predictive models directly within your query, enabling immediate, informed decision-making based on complex, combined datasets.

SurrealDB stands apart from traditional database solutions by redefining the scope of the data layer, offering structural benefits that accelerate the entire development lifecycle.

• Infrastructure Consolidation: Unlike solutions that require separate services for the database (SQL/NoSQL), graph processing, search indexing, real-time updates, and an API gateway, SurrealDB unifies all these functions. This consolidation simplifies maintenance, reduces vendor lock-in, and lowers overall cloud spend.
• Extreme Deployment Flexibility: SurrealDB is built to run anywhere your application lives. It can be deployed as a highly-scalable distributed cluster (using TiKV or SurrealKV), run in a single-node persistent mode (RocksDB), or even embedded directly into a web browser (using WebAssembly and IndexedDB persistence) or application binary, providing unparalleled versatility from testing to production.
• Native Code Execution and Extensibility: The ability to define custom functions using embedded JavaScript and to trigger complex logic via Table Events means you can push intricate business logic down to the database layer. This ensures consistency and performance, as heavy computations occur adjacent to the data source.

Conclusion

SurrealDB provides the unified power and flexibility modern developers require, simplifying infrastructure while accelerating the development of secure, real-time applications. Built to handle everything from embedded local storage to highly-scalable distributed clusters, SurrealDB is the definitive choice for developers looking to consolidate their stack and unlock new levels of performance and simplicity.