SurrealDB vs. agent databases

Q: How is SurrealDB different from HelixDB or HydraDB?

SurrealDB is a mature, multi-model database where documents, graphs, vectors, and time-series are native primitives in one engine with unified ACID transactions. Agent databases typically self-host separate graph and vector substrates without cross-model ACID, enterprise governance, or Gen 3 storage.

Q: Does SurrealDB support MCP?

Yes. The SurrealDB ecosystem provides MCP servers across the entire platform: SurrealDB for data queries, Spectron for memory, and SurrealDB Cloud for infrastructure. An agent connected to the Surreal ecosystem can query data, store and retrieve memories, and manage infrastructure through standard MCP tool calls.

Q: Is SurrealDB production-ready for agent workloads?

Yes. SurrealDB has been in development since 2018 and is used in production by Samsung, Verizon, Tencent, and PolyAI. Enterprise deployments include SOC 2 and ISO 27001 compliance, dedicated support, and SLA guarantees.

HelixDB, HydraDB, ReasonDB, and other specialist agent databases correctly identify that flat vector stores are insufficient. But combining graph and vector in one product is not the same as unifying them in one engine.

THE LANDSCAPE

Purpose-built for agents, but architecturally incomplete

A growing wave of specialist databases targets the agent memory wedge. They correctly identify that flat vector stores are insufficient, but each internalises the multi-system architecture rather than eliminating it.

HelixDB

Rust-based graph-vector database with its own query language and MCP support. Strong developer experience, but no native document model or enterprise governance.

HydraDB

Plug-and-play memory infrastructure with context evolution tracking. Graph and vector are separate internal substrates with no unified ACID transactions.

ReasonDB

AI-native document database using LLM-guided tree traversal instead of flat RAG chunks. Novel retrieval, but no graph model, no temporal versioning, no multi-model unification.

THE PROBLEM

Internalised frankenstack

These products self-host separate vector and graph substrates and fuse results at the application layer. The components have distinct consistency models.

Single transaction

Vector DB

Write embedding

Graph DB

Write relation

committed

inconsistent state

rolled back

Vector DB

Similarity search

auth

config

monitor

Graph DB

Relationship store

auth

config

monitor

Doc store

Raw document index

auth

config

monitor

Auth service

Identity & tokens

auth

config

monitor

Cache layer

Hot key store

auth

config

monitor

Five systems. Five auth configs. Five things to scale, secure, and keep alive.

No ACID across models

Graph and vector live in separate engines. Queries see inconsistent state across models.

No native document model

Every piece of data is a node or an edge. No schema-validated JSON documents with access control.

No enterprise governance

No row-level permissions, no field-level security, no schema-enforced access control.

No Gen 3 storage

Compute and storage are coupled. No scale down to zero, no instant branching, no native disaster recovery.

THE ALTERNATIVE

The only system that owns the full vertical

SurrealDB is a mature multi-model database, in development since 2018 and proven at scale by Samsung, Tencent, and enterprises across defence, finance, and healthcare. Spectron builds structured memory directly on this engine.

True ACID unification

Graph traversal, vector similarity, document operations, and temporal queries - all in one ACID transaction.

Full document model

A graph edge is a full document. Relationships carry metadata, timestamps, embeddings, and structured data.

Enterprise governance

DEFINE ACCESS with row-level permissions, field-level security, JWT auth, multi-tenant isolation. SOC 2, ISO 27001 compliant.

TRUSTED BY

Enterprise teams building on SurrealDB

From knowledge graphs to AI assistants - how enterprise teams are building on the context layer.

Samsung

Unlocking insights with knowledge graphs

Samsung Ads uses SurrealDB to build dynamic, real-time knowledge graphs for smarter campaign execution - collapsing three legacy data stores into one.

Read case study

Verizon

AI assistant empowering 10,000 technicians

Verizon uses SurrealDB to power a generative AI assistant for 10,000 field technicians, delivering instant access to documentation, outage updates, and workflows.

Read case study

Tencent

Unified infrastructure monitoring

Tencent consolidated nine backend tools into one real-time monitoring platform powered by SurrealDB's multi-model context graph.

Read case study

PolyAI

High-performance customer service AI powered by RAG

PolyAI connects SurrealDB to Agent Studio for low-latency, customer-controlled RAG across voice AI experiences.

Read case study

FREQUENTLY ASKED QUESTIONS

Agent databases

How is SurrealDB different from HelixDB or HydraDB?

Does SurrealDB support MCP?

Is SurrealDB production-ready for agent workloads?

GET STARTED

Build on proven foundations

SOC 2 Type 2

GDPR

Cyber Essentials Plus

ISO 27001