is the ultimate cloud
database for tomorrow's applications
Develop easier. Build faster. Scale quicker.
What is SurrealDB?
SurrealDB is an end-to-end cloud native database for web, mobile, serverless, jamstack, backend, and traditional applications. SurrealDB reduces the development time of modern applications by simplifying your database and API stack, removing the need for most server-side components, allowing you to build secure, performant apps quicker and cheaper. SurrealDB acts as both a database and a modern, realtime, collaborative API backend layer. SurrealDB can run as a single server or in a highly-available, highly-scalable distributed mode - with support for SQL querying from client devices, GraphQL, ACID transactions, WebSocket connections, structured and unstructured data, graph querying, full-text indexing, geospatial querying, and row-by-row permissions-based access.
View the features, the latest releases, the product roadmap, and documentation.
Contents
Features
Documentation
For guidance on installation, development, deployment, and administration, see our documentation.
Installation
SurrealDB is designed to be simple to install and simple to run - using just one command from your terminal. In addition to traditional installation, SurrealDB can be installed and run with HomeBrew, Docker, or using any other container orchestration tool such as Docker Compose, Docker Swarm, Rancher, or in Kubernetes.
Install on macOS
The quickest way to get going with SurrealDB on macOS is to use Homebrew. This will install both the command-line tools, and the SurrealDB server as a single executable. If you don't use Homebrew, follow the instructions for Linux below to install SurrealDB.
brew install surrealdb/tap/surreal
Install on Linux
The easiest and preferred way to get going with SurrealDB on Unix operating systems is to install and use the SurrealDB command-line tool. Run the following command in your terminal and follow the on-screen instructions.
curl -sSf https://install.surrealdb.com | sh
Install on Windows
The easiest and preferred way to get going with SurrealDB on Windows is to install and use the SurrealDB command-line tool. Run the following command in your terminal and follow the on-screen instructions.
iwr https://windows.surrealdb.com -useb | iex
Run using Docker
Docker can be used to manage and run SurrealDB database instances without the need to install any command-line tools. The SurrealDB docker container contains the full command-line tools for importing and exporting data from a running server, or for running a server itself.
docker run --rm --name surrealdb -p 8000:8000 surrealdb/surrealdb:latest start
For just getting started with a demonstration server running in memory, you can pass the container a basic initialization to set the user and password as root and enable logging and limit access to localhost (do not run this in production!)
docker run --rm --name surrealdb -p 127.0.0.1:8000:8000 surrealdb/surrealdb:latest start --log trace --user root --pass root memory
To update the image to the latest version:
docker pull surrealdb/surrealdb:latest
Getting started
Getting started with SurrealDB is as easy as starting up the SurrealDB database server, choosing your platform, and integrating its SDK into your code. You can easily get started with your platform of choice by reading one of our tutorials.
Client side apps
Server side code
Quick look
With strongly-typed data types, data can be fully modelled right in the database.
UPDATE person SET waist = <int> "34.59", height = <float> 201, score = <decimal> 0.3 + 0.3 + 0.3 + 0.1 ;
Store dynamically computed fields which are calculated when retrieved.
CREATE person SET birthday = "2007-06-22", can_drive = <future> { time::now() > birthday + 18y } ;
Easily work with unstructured or structured data, in schema-less or schema-full mode.
-- Create a schemafull table DEFINE TABLE user SCHEMAFULL; -- Specify fields on the user table DEFINE FIELD name ON TABLE user TYPE object; DEFINE FIELD name.first ON TABLE user TYPE string; DEFINE FIELD name.last ON TABLE user TYPE string; DEFINE FIELD email ON TABLE user TYPE string ASSERT is::email($value); -- Add a unique index on the email field preventing duplicate values DEFINE INDEX email ON TABLE user COLUMNS email UNIQUE; -- Create a new event whenever a user changes their email address DEFINE EVENT email ON TABLE user WHEN $before.email != $after.email THEN ( CREATE event SET user = $this, time = time::now(), value = $after.email, action = 'email_changed' );
Connect records together with fully directed graph edge connections.
-- Add a graph edge between user:tobie and article:surreal RELATE user:tobie->write->article:surreal SET time.written = time::now() ; -- Add a graph edge between specific users and developers LET $from = (SELECT users FROM company:surrealdb); LET $devs = (SELECT * FROM user WHERE tags CONTAINS 'developer'); RELATE $from->like->$devs UNIQUE SET time.connected = time::now() ;
Query data flexibly with advanced expressions and graph queries.
-- Select a nested array, and filter based on an attribute SELECT emails[WHERE active = true] FROM person; -- Select all 1st, 2nd, and 3rd level people who this specific person record knows, or likes, as separate outputs SELECT ->knows->(? AS f1)->knows->(? AS f2)->(knows, likes AS e3 WHERE influencer = true)->(? AS f3) FROM person:tobie; -- Select all person records (and their recipients), who have sent more than 5 emails SELECT *, ->sent->email->to->person FROM person WHERE count(->sent->email) > 5; -- Select other products purchased by people who purchased this laptop SELECT <-purchased<-person->purchased->product FROM product:laptop; -- Select products purchased by people in the last 3 weeks who have purchased the same products that we purchased SELECT ->purchased->product<-purchased<-person->(purchased WHERE created_at > time::now() - 3w)->product FROM person:tobie;
Store GeoJSON geographical data types, including points, lines and polygons.
UPDATE city:london SET centre = (-0.118092, 51.509865), boundary = { type: "Polygon", coordinates: [[ [-0.38314819, 51.37692386], [0.1785278, 51.37692386], [0.1785278, 51.61460570], [-0.38314819, 51.61460570], [-0.38314819, 51.37692386] ]] } ;
Write custom embedded logic using JavaScript functions.
CREATE film SET ratings = [ { rating: 6, user: user:bt8e39uh1ouhfm8ko8s0 }, { rating: 8, user: user:bsilfhu88j04rgs0ga70 }, ], featured = function() { return this.ratings.filter(r => { return r.rating >= 7; }).map(r => { return { ...r, rating: r.rating * 10 }; }); } ;
Specify granular access permissions for client and application access.
-- Specify access permissions for the 'post' table DEFINE TABLE post SCHEMALESS PERMISSIONS FOR select -- Published posts can be selected WHERE published = true -- A user can select all their own posts OR user = $auth.id FOR create, update -- A user can create or update their own posts WHERE user = $auth.id FOR delete -- A user can delete their own posts WHERE user = $auth.id -- Or an admin can delete any posts OR $auth.admin = true ;
Why SurrealDB?
Database, API, and permissions
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.
Tables, documents, and graph
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.
Advanced inter-document relations and analysis. No JOINs. No pain.
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.
Simple schema definition for frontend and backend development
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.
Connect and query directly from web-browsers and client devices
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.
Query the database with the tools you want
Your data, your choice. 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.
Realtime live queries and data changes direct to application
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.
Scale effortlessly to hundreds of nodes for high-availability and scalability
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.
Extend your database with JavaScript functions
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.
Designed to be embedded or to run distributed in the cloud
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, the system requirements have been specifically thought through for running in all types of environment.
Community
Join our growing community around the world, for help, ideas, and discussions regarding SurrealDB.
Contributing
We would for you to get involved with SurrealDB development! If you wish to help, you can learn more about how you can contribute to this project in the contribution guide.
Security
For security issues, view our vulnerability policy, view our security policy, and kindly email us at security@surrealdb.com instead of posting a public issue on GitHub.
License
Source code for SurrealDB is variously licensed under a number of different licenses. A copy of each license can be found in each repository.
For more information, see the licensing information.
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