SurrealDB offers a dynamic and adaptable platform for business. With an integrated suite of cutting-edge database solutions, tools, and services, SurrealDB empowers your workforce to discover innovative answers using products meticulously crafted to meet their requirements.
SurrealDB combines the database layer, the querying layer, and the API and authentication layer into one platform. Advanced table-based and row-based customisable access permissions allow for granular data access patterns for different types of users. There's no need for custom backend code and security rules with complicated database development.
SurrealDB is designed to be flexible to use, with support for SurrealQL, GraphQL (coming soon), CRUD support over REST, and JSON-RPC querying and modification over WebSockets. With direct-to-client connection with in-built permissions, SurrealDB speeds up the development process, and fits in seamlessly into any tech stack.
Connect directly to SurrealDB from any end-user client device. Run SurrealQL queries directly within web-browsers, ensuring that users can only view or modify the data that they are allowed to access. Highly-performant WebSocket connections allow for efficient bi-directional queries, responses and notifications.
With full graph database functionality, SurrealDB enables more advanced querying and analysis. Records (or vertices) can be connected to one another with edges, each with its own record properties and metadata. Simple extensions to traditional SQL queries allow for multi-table, multi-depth document retrieval, efficiently in the database, without the use of complicated JOINs and without bringing the data down to the client.
SurrealDB can be run as a single in-memory node, or as part of a distributed cluster - offering highly-available and highly-scalable system characteristics. Designed from the ground up to run in a distributed environment, SurrealDB makes use of special techniques when handling multi-table transactions, and document record IDs - with no use of table or row locks.
As a multi-model database, SurrealDB enables developers to use multiple techniques to store and model data, without having to choose a method in advance. With the use of tables, SurrealDB has similarities with relational databases, but with the added functionality and flexibility of advanced nested fields and arrays. Inter-document record links allow for simple to understand and highly-performant related queries without the use of JOINs, eliminating the N+1 query problem.
With SurrealDB, specify your database and API schema in one place, and define column rules and constraints just once. Once a schema is defined, database access is automatically granted to the relevant users. No more custom API code, and no more GraphQL integration. Simple, flexible, and ready for production in minutes, not months.
SurrealDB keeps every client device in-sync with data modifications pushed in realtime to the clients, applications, end-user devices, and server-side libraries. Live SQL queries allow for advanced filtering of the changes to which a client subscribes, and efficient data formats, including DIFFing and PATCHing enable highly-performant web-based data syncing.
Embedded JavaScript functions allow for advanced, custom functionality, with computation logic being moved to the data layer. This improves upon the traditional approach of moving data to the client devices before applying any computation logic, ensuring that only the necessary data is transferred remotely. These advanced JavaScript functions, with support for the ES2020 standard, allow any developer to analyse the data in ever more simple-yet-advanced ways.
Built entirely in Rust as a single library, SurrealDB is designed to be used as both an embedded database library with advanced querying functionality, and as a database server which can operate in a distributed cluster. With low memory usage and cpu requirements, SurrealDB has been specifically designed to run in all types of environment.
"Here at Yaacomm we are already using SurrealDB in a significant way for our backend infrastructure, however I believe SurrealDB can play an even bigger role in other areas as well. Being able to embed SurrealDB locally in Android and iOS apps could make it a perfect fit for local caching. Additionally, this would provide us with all the benefits of SurrealDB such as full-text searching and its graph based nature without relying on a network connection."
"It think it's going to change how we query databases."
Director, Partner Delivery Success, C360 Cross-Cloud, Salesforce
"Throughout my years dealing with database challenges, SurrealDB seems to be a beacon of innovation. Addressing issues like multi-tenancy, blending the best of hybrid & distributed databases, and ensuring unmatched scalability & performance. Oh and btw it had ML integrated in the database - how cool is that! But the true standout? Live queries and change feeds. Such features are not just advancements, they're revolutions in how we handle data. Goes to show the evolution of databases are not over yet!!"
R&D Principal Technologist, Aveva
"It's incredible what SurrealDB provides and also what's coming up in the near future. Embedding, scaling, machine learning, live queries... SurrealDB as an event store or persisted broker or IoT platform - I've so many ideas right now for the next project. Awesome!"
Senior Developer
"SurrealDB looks amazing. Cloud-native Database written in Rust using SQL for structured and unstructured data, graph querying, full-text indexing, and geospatial querying, while supporting row-level permissions."
Co-founder and CTO, Qualia
"Now that it's at 1.0, there is a pretty good use case to using it in some serious projects."
Web Developer and Tech Influencer, Fireship
"Exciting things are happening in the Tech industry. Bun just announced version 1.0 is prod ready. And now SurrealDB is launching stable version 1.0. This is the most significant shift in my decade-long developer experience. Excited to see what's next!"
Lead Software Engineer, Figment
"It's fast, small, can run on browser, edge and cloud. It can handle large data. It can run in-memory like redis or disk like sqlite and it can run multi-cluster. It can sync between cloud and edge. And to top of it off, it can also run as a graphdb. It's interesting."
CTO, IBM iX
"Very excited to put these capabilities into practice."
Principal Engineer, Vivint
