Unifies multi-model data for AI agents with a single, ACID-compliant transaction layer.
Product memo
SurrealDB provides a unified context layer for AI agents, consolidating documents, graphs, vectors, and time-series data into a single ACID-compliant engine. This eliminates the need for multiple databases and middleware, offering a direct transaction from storage to memory. It simplifies development and enhances AI reasoning capabilities by ensuring data consistency across diverse models.
For who
AI agents and developers
Solves what
Unifies multi-model data (docs, graphs, vectors, time-series) into a single ACID transaction.
- Multi-model database
- Single ACID transaction
- Context layer for AI
In their own words
The context layer
The database where storage, context, and memory are one transaction.
Commercial cues
Model
free only
Free tier
Yes
Trial
No
Pricing Strategy
The 'Start' tier offers a free forever option with 1GB of storage, allowing developers to build and prototype. Larger deployments move to custom quotes for 'Scale', 'Enterprise'.
- • A free tier with 1GB storage removes adoption friction for individual developers.
- • Scale handles custom requirements.
- • Monthly pricing keeps plan comparison straightforward.
Operator context
Operating setup
Founded
May 2025
Platform
Web app
Audience
Developers
Social footprint
Tech stack
Market demand
Surrealdb keyword demand
5 keywords
Market demand is Starter-tier market intelligence.
Derived from this product’s latest SimilarWeb keyword mix — directional demand, not proof.
Builder Strategy
- Strategy Type
- Niche Specialist
- Stage
- Vc Growth
- Effort
- Small Team
About Surrealdb Expand
SurrealDB offers a multi-model database designed specifically for AI agents and developers. It unifies diverse data types — including documents, graphs, vectors, and time-series data — into a single ACID-compliant transaction.
This approach simplifies the backend for AI applications by providing a cohesive context layer, eliminating the need to manage multiple specialized databases. Developers benefit from a simplified data architecture that ensures consistency and improves the reliability of AI reasoning.
The product's positioning around a unified data model addresses a core challenge in building complex AI systems.