What query language does the SurrealDB server use?

SurrealQL. The query tool runs arbitrary SurrealQL statements with parameter binding, and select, create, update, and delete cover reads and writes. relate adds graph edges when the data model calls for them.

Why is SurrealDB fourth among NoSQL databases?

It is multi-model, mixing documents, graphs, and relations, which trades depth in any one shape. MongoDB leads for documents, Redis for in-memory key-value and vectors, and Couchbase for distributed documents. SurrealDB fits apps that genuinely need several shapes in one store.

SurrealDB for NoSQL databases

Pick 4 of 4 for NoSQL databasesOfficialSurrealDB

Among NoSQL databases, SurrealDB is our fourth pick of four, and it fits a distinct shape rather than a mainstream one: a multi-model app that mixes documents, graphs, and relations in a single store. Its official server lets an agent query and mutate an instance with SurrealQL and manage SurrealDB Cloud, which is the draw for teams who do not want to split data across several engines.

MongoDB leads as the document database most NoSQL work centers on, Redis covers the in-memory key-value and vector case, and Couchbase the distributed document store. SurrealDB earns the spot when one unified query language across several data shapes matters more than depth in any one.

How SurrealDB fits

The tools that fit NoSQL work are query, which runs arbitrary SurrealQL with parameter binding, and select, which reads records from a table or by id, so an agent can inspect a document and explain the result in one turn. create, insert, upsert, update, and delete cover writes across the data shapes, and relate adds graph edges when the model needs them. connect_endpoint and disconnect_endpoint handle the connection at runtime, while use_namespace and use_database set the active scope before a query runs.

The honest limit: SurrealDB spreads across documents, graphs, and relations, so it trades the depth a single-purpose engine offers. MongoDB, the top pick, is the mature document store with the broadest NoSQL tooling; Redis is the choice for in-memory key-value and vector workloads; Couchbase covers distributed document use. Because NoSQL queries are easy to get subtly wrong, note that SurrealQL is its own language to learn. Choose SurrealDB when an app genuinely mixes shapes and you want one store and one query language the agent drives, rather than the deepest support for any single model.

Tools you would use

Tool	What it does
query	Runs an arbitrary SurrealQL statement against the connected instance, with parameter binding.
select	Selects records from a table or by record ID.
insert	Inserts one or more records into a table.
create	Creates a single record with the given content.
upsert	Inserts a record or updates it if it already exists.
update	Updates existing records with new content.
delete	Deletes records from a table or by record ID.
relate	Creates a graph edge relating two records.
connect_endpoint	Connects to a SurrealDB endpoint at runtime.
disconnect_endpoint	Disconnects from the current SurrealDB endpoint.

Full SurrealDB setup and config →

FAQ

What query language does the SurrealDB server use?: SurrealQL. The query tool runs arbitrary SurrealQL statements with parameter binding, and select, create, update, and delete cover reads and writes. relate adds graph edges when the data model calls for them.
Why is SurrealDB fourth among NoSQL databases?: It is multi-model, mixing documents, graphs, and relations, which trades depth in any one shape. MongoDB leads for documents, Redis for in-memory key-value and vectors, and Couchbase for distributed documents. SurrealDB fits apps that genuinely need several shapes in one store.