SurrealDB vs. traditional databases

Q: Can SurrealDB replace Postgres or MySQL?

Yes. SurrealDB supports relational queries, SQL-like syntax, ACID transactions, and structured schemas. It also adds native graph traversal, vector search, temporal queries, and agent memory - capabilities that traditional databases require extensions or separate systems to achieve.

Q: What about bi-temporal versioning?

SurrealDB supports native bi-temporal versioning with transaction time (when data was committed) and valid time (when data is considered valid in the real world). Traditional databases store only current state - previous values are lost on update.

Q: How does Gen 3 storage reduce costs?

Gen 3 storage uses commodity cloud object storage instead of provisioned disk, stateless compute that scales to zero when idle, and routes data through object storage to reduce cross-AZ network costs. Development and staging environments cost nothing when inactive.

Three generations of database architecture for the AI era. From single-model silos to the unified data layer.

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THE GAP

What traditional databases miss

Traditional databases support one model well, but not native graph traversal, vector search, temporal queries, or unified multi-model execution. As AI workloads grow, teams bolt on extensions, glue systems together, and manage ever-growing operational complexity.

No native graphs

Postgres requires joins and CTEs. Graph traversal is a workaround, not a first-class feature.

No native vectors

Extensions like pgvector are bolt-ons. Not designed for hybrid queries or agent workloads.

No temporal awareness

No bi-temporal versioning. Can't query “what did we know when?”

THE SOLUTION

Everything in one engine

SurrealDB was designed from the ground up as a native multi-model engine. Documents, graphs, vectors, time-series, and geospatial data - all first-class, all in one query language, one transaction boundary.

Native multi-model

Documents, graphs, vectors, time-series, geospatial. All first-class, all in one engine.

SurrealQL

One query language for everything. SQL-like, familiar, powerful. No glue code between models.

ACID across models

One transaction boundary. Update a document and its graph relationships atomically.

Agent-ready

Agent memory for memory. Knowledge graphs, entity extraction, temporal facts - built into the database.

STORAGE ARCHITECTURE

Three generations of database infrastructure

The database industry is undergoing a generational shift driven by cloud object storage, elastic compute, and AI workloads.

Gen 1: Monolith

Compute and storage tightly coupled inside a single machine. Scaling means buying a bigger box.

MySQL, PostgreSQL (self-hosted), classic Oracle

Gen 2: Proprietary loose coupling

Cloud vendors separated storage from compute, but data remains locked in proprietary formats with cloud lock-in.

Amazon Aurora, Oracle Exadata, Google AlloyDB

Gen 3: Open storage on the lake

Data lives in commodity cloud object storage in open formats. Compute runs independently as stateless, elastic instances.

Databricks Lakebase, SurrealDB

TRUSTED BY

Saks Fifth Avenue uses SurrealDB's vector search and graph capabilities to deliver real-time, AI-powered personalisation across 5 million luxury customers and 45 million monthly product-recommendation queries.

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FREQUENTLY ASKED QUESTIONS

Traditional databases

Can SurrealDB replace Postgres or MySQL?

What about bi-temporal versioning?

How does Gen 3 storage reduce costs?

GET STARTED

Move to Generation 3

The ACID rigor of traditional databases with the elasticity, durability, and economics of modern cloud infrastructure.

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