Build real-time apps faster
with the world's most powerful
multi-model database

Zero maintenance. Zero hassle.

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One platform,
unlimited possibilities

Multi-model: for all types of data

Handle relational, document, graph, time series, key value, vector and search, in one place.

Simplicity that scales

Scale compute and storage separately, from 0 to 100s of nodes and back to 0, without sharding.

Superior developer experience

SurrealQL is intuitive and easy to learn, blending SQL familiarity with modern flexibility.

AI made easy

Build generative AI apps with vectors, knowledge graphs, and in-database ML capabilities.

Transactional and analytical

Built for data intensive applications and real-time analytics.

Advanced security

Built-in access controls, granular table, row and field-level permissions.

Learn the SurrealDB Basics

Query the way you want without
switching between databases

SurrealQL

SELECT name, ->order->product.{name, price}
FROM person

SQL


SELECT p.name, pr.name, pr.price 

FROM person p 

INNER JOIN order o ON p.id = o.person_id 

LEFT JOIN product pr ON o.product_id = pr.id

SurrealQL

SELECT
    rating,
    review_text,
    person.name,
    person.email
FROM review:01FXNDZ2C893992S408TX4MYYQ

MQL

db.review.aggregate([
    {
        "$match": {
            "_id": "01FXNDZ2C893992S408TX4MYYQ"
        }
    },
    {
        "$lookup": {
            "from": "person",
            "localField": "person",
            "foreignField": "_id",
            "as": "person"
        }
    },
    {
        "$project": {
            "_id": 0,
            "rating": 1,
            "review_text": 1,
            "person.name": 1,
            "person.email": 1
        }
    }
])

SurrealQL

SELECT name, ->order->product.{name, price}
FROM person

Cypher


MATCH (p:Person)-[:ORDER]->(pr:Product) 

RETURN p.name, pr.name, pr.price

Learn about SurrealQL

Built by developers,
loved by developers

"I think it's going to change how we query databases."

Anup Jadhav

Director, Salesforce

"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."