SurrealDB vs CockroachDB
These two MCP servers connect an agent to very different distributed databases, even though both promise to scale beyond a single node. SurrealDB's official server speaks SurrealQL against a multi-model engine that unifies document, graph, relational, and vector data behind one query language, and it can also manage SurrealDB Cloud instances. The CockroachDB server is a community-built, natural-language interface to CockroachDB, the distributed, PostgreSQL-compatible SQL database, and it goes well beyond querying into schema management and live cluster-health monitoring. So the choice is partly about the data model you want the agent to work in — SurrealDB's flexible multi-model world versus CockroachDB's strict, Postgres-compatible relational SQL — and partly about how much operational surface you want to expose. Here is how the two compare when you wire an agent into them.
How they compare
| Dimension | SurrealDB | CockroachDB |
|---|---|---|
| Data model | Multi-model: document, graph, relational, and vector data unified behind SurrealQL, so an agent can relate records and run vector search in one engine. | Strictly relational and PostgreSQL-compatible — the agent works in standard SQL with tables, transactions, and familiar Postgres semantics. |
| Query language | SurrealQL via a dedicated query tool, plus structured select/insert/create/upsert/update/delete and a relate operation for graph edges. | Standard SQL through execute_query and execute_transaction, with explain_query and explain plans an agent can read. |
| Cluster operations | Cloud-focused: list cloud organizations and instances, and create, pause, resume, or check the status of SurrealDB Cloud instances from the agent. | Deep self-managed cluster observability: cluster status, running and slow queries, replication status, contention events, and index recommendations. |
| Tool surface | Around twenty tools centered on data operations plus namespace/database switching and cloud lifecycle management. | A very broad surface spanning four areas — querying, transactions, schema evolution (create/drop tables, indexes, views), and node-level monitoring. |
| Official vs community | Official SurrealDB server, so it tracks the engine and Cloud platform directly. | Community server (amineelkouhen) that wraps CockroachDB's Postgres wire protocol with a rich, opinionated toolset. |
Verdict
Choose by the database that backs your application and how much you want the agent to do. SurrealDB's server is the right pick when you run SurrealDB and want an agent fluent in its multi-model, SurrealQL world — relating documents and graph edges, doing vector search, and spinning Cloud instances up and down. The CockroachDB server fits when your data lives in CockroachDB and you want a Postgres-compatible SQL agent that can also evolve schema and watch the health of a multi-node cluster, including slow queries and replication. They are not interchangeable: pick the one whose engine you actually run, and weigh SurrealDB's official, data-first surface against CockroachDB's broader, community-built operational reach.
FAQ
- Are both of these for distributed databases?
- Both target databases designed to scale across nodes, but the engines differ: SurrealDB is multi-model with SurrealQL, while CockroachDB is a distributed, PostgreSQL-compatible relational SQL database.
- Which exposes more operational tooling?
- The CockroachDB server has a broader operational surface, including cluster status, slow-query and contention monitoring, and index recommendations, whereas SurrealDB focuses on data operations plus SurrealDB Cloud instance lifecycle.