OBJECT STORAGE

Storage that scales with you

Read the docs Start free with SurrealDB

Embedded. A local engine, in process.

Distributed. Compute apart from storage, in a fault-tolerant cluster.

Files. First-class across every backend.

From a single binary to a distributed cluster.The same engine runs embedded in your application or across a cluster, with compute and storage scaling apart. The distributed layer ships in SurrealDB Enterprise and SurrealDB Cloud; the community edition runs the embedded engines.

Read the docs

Embedded engines

SurrealDB in-process over SurrealKV or RocksDB, for local and edge workloads.

Explore

Compute-storage separation

Scale query nodes and storage independently, each to its own load.

Explore

Object-storage backends

Compute over S3-compatible object storage, with S3, Google Cloud Storage and Azure Blob bucket backends from 3.3.

Explore

Built-in durability

Replication and object-storage durability carry data through node loss; the engine handles recovery.

Explore

File buckets

Put, get, copy and delete uploads as records, permissioned and transactional in SurrealQL.

Explore

Versioned reads

MVCC storage keeps history, so VERSION queries read the database as it was at a point in time, on a versioned storage engine (experimental).

Explore

STORAGE ENGINES

One interface, pluggable backends

An in-memory engine for a test, a local file for a single node, a distributed backend for production, and files managed in SurrealQL throughout.

PLUGGABLE ENGINES

Start anywhere, move without rewrites

# In-memory: fast, ephemeral, ideal for tests
surreal start memory

# SurrealKV: embedded, versioned, single node
surreal start surrealkv://production.db

# RocksDB: embedded, high-throughput
surreal start rocksdb://production.db

FILE BUCKETS

Files, defined and queried like data

DEFINE BUCKET uploads BACKEND "memory";

f"uploads:/readme.txt".put("SurrealDB");
f"uploads:/readme.txt".get();
f"uploads:/readme.txt".copy("uploads:/readme.backup.txt");

Files and data in one system

One permission model

Buckets and records share access control, so a file is guarded by the rules of the row that references it.

Each layer on its own

Compute apart from storage adds query capacity or durable capacity independently.

File handling is SurrealQL

Uploads are queried, permissioned and transacted in the same language as the data.

Everything an application and its agents know. Five surfaces, one engine.

Database

Document, graph, vector, time-series and relational in one engine.

Five data models as dotted tiles: documents, graph, vector, time-series and relational

Agent Memory

What an agent learns, with its source and its time, in the same engine.

A timeline of remembered facts, each with its source

Cloud

Managed clusters in the regions you choose, scaled on demand.

Clusters in three regions on a world map, each running or scaling

Studio

Query, explore and design the schema from the browser.

MCP

Every model that speaks MCP reaches the database and the memory directly.

Three models connected through MCP to the database and Agent Memory

IN PRODUCTION

Trusted at scale. Samsung, Nvidia, Verizon, Tencent, and Walmart run on SurrealDB.

14,000+

Developers building on SurrealDB Cloud

4M+

Developers building on SurrealDB worldwide

FROM THE TEAMS

SurrealDB gives us a foundation where we can unify semantic search, knowledge graphs, and AI-driven decision making without stitching together multiple systems. Collapsing responsibility into SurrealDB has become our default engineering posture.

Justin Foley

VP of Engineering, Later

GET STARTED

Store everything in one engine. Embedded or distributed, with files and data in the same SurrealQL.

Read the docs Start free with SurrealDB

Storage that scales with you

From a single binary to a distributed cluster.The same engine runs embedded in your application or across a cluster, with compute and storage scaling apart. The distributed layer ships in SurrealDB Enterprise and SurrealDB Cloud; the community edition runs the embedded engines.

Embedded engines

Compute-storage separation

Object-storage backends

Built-in durability

File buckets

Versioned reads

One interface, pluggable backends

Start anywhere, move without rewrites

Files, defined and queried like data

Files and data in one system

One permission model

Each layer on its own

File handling is SurrealQL

Keep exploring

Technical deep dive

Deployment documentation

All features

Everything an application and its agents know. Five surfaces, one engine.

Trusted at scale. Samsung, Nvidia, Verizon, Tencent, and Walmart run on SurrealDB.

Store everything in one engine. Embedded or distributed, with files and data in the same SurrealQL.