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
SurrealDB in-process over SurrealKV or RocksDB, for local and edge workloads.
Compute-storage separation
Scale query nodes and storage independently, each to its own load.
Object-storage backends
Compute over S3-compatible object storage, with S3, Google Cloud Storage and Azure Blob bucket backends from 3.3.
Built-in durability
Replication and object-storage durability carry data through node loss; the engine handles recovery.
File buckets
Put, get, copy and delete uploads as records, permissioned and transactional in SurrealQL.
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).
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.
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
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
Each layer on its own
File handling is SurrealQL
THE PLATFORM
Everything an application and its agents know. Five surfaces, one engine.
Database
Document, graph, vector, time-series and relational in one engine.
Agent Memory
What an agent learns, with its source and its time, in the same engine.
Cloud
Managed clusters in the regions you choose, scaled on demand.
Studio
Query, explore and design the schema from the browser.
MCP
Every model that speaks MCP reaches the database and the memory directly.
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.
VP of Engineering, Later
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