NoSQL Databases · Reviewed 21 Oct 2026

SurrealDB

Multi-model database for applications and AI agents.

free tier · surrealdb.com ↗

Paid against free › NoSQL Databases › SurrealDB

SurrealDB at a glance

Overview

01

Summary

The useful answer before the supporting detail.

SurrealDB is a multi-model database that stores relational, document, graph, time-series, vector, and full-text data in one engine, queried through SurrealQL S27. It is used by developers building applications and AI agents, with a managed cloud and an Agent Memory layer for AI agent memory S1 S54. The engine is free to self-host under BSL 1.1, with SDKs and tools open source, and offers a cloud with usage-based pricing S1 S29.

02

Product identity and positioning

Name, category, positioning, audience, and first-party claims.

  • Identity: SurrealDB is a multi-model database for applications and AI agents S1.
  • Core purpose: It solves the problem of fragmenting data across multiple databases by unifying relational, document, graph, time-series, vector, and full-text data in one engine S27.
  • Intended users: Developers building applications and AI agents S1.
  • Product scope: It is a database engine that runs embedded, as a single node, or as a distributed cluster, with a managed cloud and an Agent Memory layer S27 S54.
  • Positioning: The company positions it as the database for applications and AI agents, built in the open S1.
  • Claimed distinction: It claims to offer graph, vector, and full-text from one engine, avoiding stack fragmentation S1.
03

Use cases and audiences

Who the product serves and the jobs it is designed to handle.

AudiencePractical use case
Application developersBuild applications with a single engine that handles relational, document, graph, vector, and full-text data S27.
AI agent developersGive agents persistent memory and knowledge with SurrealDB Agent Memory S54.
StartupsAvoid fragmenting the stack by using one engine for graph, vector, and full-text capabilities S1.
Enterprise teamsRun fault-tolerant, multi-zone clusters with FIPS-validated cryptography and contractual support S49.

Features

09

Features and capabilities

Core functions and evidence-backed product capabilities.

CapabilityWhat it does
Multi-model data storageStores relational, document, graph, time-series, vector, and full-text data in one engine, queried via SurrealQL S27.
SurrealQL query languageSQL-shaped query language that reads intuitively, with a full reference for every statement and method S27.
Capabilities-based securityControls features like scripting, functions, and network access per instance, denying all by default unless allowed S39.
Agent MemoryProvides a memory and knowledge layer for AI agents, with retrieval, traces, and time-based decay S54.
Agent setup with MCPConnects agents to SurrealDB via Agent Skills and MCP, with official skills for SurrealQL, vector search, and the Python SDK S62.
Enterprise fault toleranceOffers always-on clusters across availability zones, with distributed live queries and FIPS 140-2 validated cryptography S49.
10

Integrations and ecosystem

Connected products, exports, APIs, and workflow compatibility.

Integration or interfaceTypeWhat it enables
Official SDKsSDKConnect from ten official SDKs to query and manage the database S27.
MCP serverAI interfaceConnects agents to SurrealDB Cloud to deploy, query, and monitor instances S62.
Agent SkillsAI interfaceProvides packaged knowledge of SurrealDB behavior for agents, covering SurrealQL, vector search, and Python SDK S62.
PostgreSQL and MongoDB importData portabilityImport data and schemas from PostgreSQL, MongoDB, and other databases S65.
AWS MarketplaceIntegrationSubscribe to SurrealDB Cloud through AWS, with billing via AWS console S29.
Azure MarketplaceIntegrationSubscribe through Azure, with billing via Azure portal S29.

Pricing

11

Pricing and plans

Published plans, free access, trials, credits, and pricing limitations.

Plan or offerVerified price and billingIncludedLimits
Start, first instance$0 per hour, hourly S291 GB storage S290.25 vCPU, 1 GB memory S29
Start, further instancesFrom $0.021 per hour, hourly S29Storage priced separately S29Vertical scaling only S29
Scale$0.192 per node hour, hourly S29Not published S29Three nodes minimum, multi-zone S29
EnterpriseCustom, custom billing S29Not published S29Self-hosted, FIPS, audit logging S29
Free tierFirst instance free S290.25 vCPU, 1 GB memory, 1 GB storage, 1 GB egress S29Not established S29

Competition

12

Competitive landscape

Domains competing for the same organic search demand.

Sampled competitors

CompetitorFirst-page appearancesSampled queriesAverage positionQueries observed
deltawaterfowl.org111fetch table
youtube.com112fetch table
github.com112surrealdb
forum.gon.com113fetch table
reddit.com113surrealdb
michigan-sportsman.com114fetch table
x.com114surrealdb
postgresql.org115fetch table
uk.linkedin.com115surrealdb
facebook.com116fetch table

Website intelligence — Collected evidence

Customers, testimonials, and first-party review claims

No supporting public-page evidence was collected for this category.

Independent review sources discovered

No links to supported independent review platforms were discovered on the collected pages.

14

AI visibility

Measured ChatGPT and Google AI mentions with cited sources.

AI-assistant referral traffic

  • Estimated current generative-AI referral share: 1.2%

Scout traffic model did not return a separate AI-referral trend series for this domain.

Website intelligence — Collected evidence

Site-stated AI capabilities

Page typeEvidenceSource
otherSurrealDB is a multi-model database and an Agent Memory layer: one engine for your application's data and durable, provable memory for your AI agents.https://surrealdb.com/
otherlayer for AI agentshttps://surrealdb.com/
otherAn AI assistant for 10,000 technicianshttps://surrealdb.com/
other> As a startup, we didn't want to fragment our stack every time we add a capability… instead we got graph, vector, and full-text from one engine. What surprised us was how quickly we stood up a multi-layered, graph-based memory model for our AI agent.https://surrealdb.com/
featuresRun data, logic, and AI directly in edge devices or browsers for low-latency, offline-ready workloads.https://surrealdb.com/solutions
featuresReal-time personalisation and vendor content for AI-driven retail platforms.https://surrealdb.com/solutions
featuresAI & AGENTSMemory layers for LLM agentshttps://surrealdb.com/solutions
featuresEnhance LLM agents with both structured memory graphs and semantic recall for richer, more contextual interactions.https://surrealdb.com/solutions
featuresAn AI assistant for 10,000 technicianshttps://surrealdb.com/solutions
features> As a startup, we didn't want to fragment our stack every time we add a capability… instead we got graph, vector, and full-text from one engine. What surprised us was how quickly we stood up a multi-layered, graph-based memory model for our AI agent.https://surrealdb.com/solutions/graph-rag
featuresAI-native. Vector, full-text and graph retrieval, built in.https://surrealdb.com/surrealdb/features
featuresAI agents. Structured context and persistent memory in one engine.https://surrealdb.com/solutions
featuresFrom AI agents to knowledge graphs. On one data layer.https://surrealdb.com/solutions
featuresBuild generative AI apps and multi-step AI agents with unified context, memory, and action in one place.https://surrealdb.com/solutions
features](/use-cases/ai-agents)[https://surrealdb.com/solutions
featuresRun data, logic, and AI directly in edge devices or browsers for low-latency, offline-ready workloads.https://surrealdb.com/solutions
featuresAI-native. Vector, full-text and graph retrieval, built in.https://surrealdb.com/surrealdb/features
features[Architecture and storage](#architecture-and-storage)[Database engine](#database-engine)[Indexing and search](#indexing-and-search)[Data model](#data-model)[Query language](#query-language)[Machine learning](#machine-learning)[File storage](#file-storage)[AI agents](#ai-agents)[Functions and extensibility](#functions-and-extensibility)[Security and authorisation](#security-and-authorisation)[Connectivity](#connectivity)[Tooling](#tooling)[Deployment options](#deployment-options)[Observability and monitoring](#observability-and-monitoring)[Trust and compliance](#trust-and-compliance)[SDKs](#sdks)https://surrealdb.com/surrealdb/features
integrationsAlready using an AI agent?https://surrealdb.com/docs
integrations](/docs/build/integrations/ai-frameworks/dagster)[https://surrealdb.com/integrations

These are first-party product claims, not independent measurements of AI-search visibility.

15

Marketing opportunities

Actions calculated directly from the collected evidence.

OpportunityRecommended actionEvidence
Competitor gap1 first-page appearances across fetch table

Website intelligence — Collected evidence

Website evidence gaps

  • customers: no usable public page was collected; verify whether the site publishes this evidence.
  • reviews: no usable public page was collected; verify whether the site publishes this evidence.
  • changes: no usable public page was collected; verify whether the site publishes this evidence.
  • identity: no usable public page was collected; verify whether the site publishes this evidence.
  • technical: no usable public page was collected; verify whether the site publishes this evidence.

Trust and proof

16

Customers, proof, and reviews

Published proof, customer signals, and review evidence.

Independent reviews

PlatformPageHow it was foundNote
Product HuntSurrealDB: Storage, context, and memory. One database, one transaction. / Product HuntGrounded web searchSurrealDB is praised for its versatility and ease of use, with a SQL-like query language that simplifies complex data exploration. Makers of SiteForge - AI Website Wireframer and 21n highlight its multi-modality and embeddability, enabling efficient data handling and fast search results. Users appreciate its intuitive interface and supportive community, noting its potential to become a leading choice despite some minor issues. Overall, SurrealDB is seen as a powerful, flexible database solution.
Independent BlogSurrealDB Experience (WIP)Grounded web searchWith that being said, I want to conclude that if unnecessary, e.g. your products database doesn’t need to utilize the flexibility of SurrealDB, doesn’t need graph-like storage, or does not have many polymorphic relations, you probably don't need it, and shouldn't be using SurrealDB as it's a lot of hassle. You'll be better off using PrismaORM with Postgres. I also want to recommend the SurrealDB team focus on working to improve the quality of these SDKs and dev tools, maybe taking official respo

Customer proof

Proof typeNamed customer or sourceEvidence
Case studySamsung, Verizon, Tencentcustomer case study — # Built on SurrealDB, running at scale Samsung. (Built on SurrealDB, running at scale)
TestimonialFountaintestimonial — Fountain is a podcast app where listeners earn and send Bitcoin over the Lightning network as they listen. (Simplifying social infrastructure with SurrealDB)

Independent mentions

External links were grounded in one live web search. Search snippets are leads, not independently scraped page content; rejected links remain available in Review evidence.

17

Company, security, and trust

Ownership, policies, security signals, and public trust evidence.

SignalFindingSource
Company and ownershipFounded. In London, by Tobie and Jaime Morgan Hitchcock.source
Contact and supportPay for what you use, billed monthly on compute, storage and network, with no upfront cost or minimum. Volume and commitment discounts are available for larger workloads; contact us for details.source
Legal and privacyYes. GDPR, CCPA, ISO 27001, SOC 2 (Type 1 and Type 2) and Cyber Essentials Plus compliant, with data encrypted at rest and in transit. The full status is at our Trust Centre.source
Security and complianceEncrypted backups, with fast point-in-time recovery.source
Uptime and status page/ Contractual support / Support tiers with defined response times by severity, and uptime commitments. / Contact sales /source
Domain registered2016-04-11—
Domain expires2027-04-11—

Every trust signal above is backed by a collected page or a registration record.

18

Documentation and product updates

Help resources, product guidance, and visible changes over time.

Resource or updateTypeWhat is availableDate or freshness
Getting started / DatabaseDocumentationThe official documentation for SurrealDB, a multi-model database. Built for modern applications. (source)Not dated
Billing / Organisations / DatabaseDocumentationPayment methods, discount codes, invoices, and the usage behind them. (source)Not dated
Capabilities / Authorization / DatabaseDocumentationSurrealDB is secure by default and is suitable for all database use cases. It offers powerful features like scripting, functions or network access from within your SurrealQL queries. (source)Not dated
Enterprise Edition Database / Products / DatabaseDocumentationWhat Enterprise Edition adds over Community: fault-tolerant multi-zone clusters, storage and compute that scale independently, distributed live queries, audit logging, FIPS-validated cryptography, trusted execution and contractual support, plus the licence key it needs to start, the SURREAL_LICENSE_* variables and the Docker Hub image. (source)Not dated
Agent Memory / Get started / Agent MemoryDocumentationMemory and knowledge for AI agents on SurrealDB. Principles, architecture, quickstarts, and the mental model. (source)Not dated
Agent setup / DatabaseDocumentationConnect your agents to SurrealDB with Agent Skills and MCP. (source)Not dated
Build / DatabaseDocumentationPutting SurrealDB into an application: embedding the engine. Migrating from another database, connecting frameworks, and wiring it to AI agents. (source)Not dated
Explore / DatabaseDocumentationSurrealDB Studio, the SurrealDB CLI, video tutorials and demos, and worked examples. Machine-learning models, and the SurrealDB Labs archive. (source)Not dated

Not found in the collected public sources: public roadmap, changelog or release notes, status page, separate help center or knowledge base.

Technical

19

Technical and delivery signals

Delivery model, platforms, API, data ownership, reliability claims and release activity.

SignalFindingSource
Delivery model (cloud, self-hosted, desktop, browser extension)SurrealDB runs embedded in applications, as a single node, or as a distributed cluster, and is available as a managed cloud S27 S29.S27 S29
Platforms and appsThe cloud is accessed via web-based SurrealDB Studio S29.S29
API and extensibility (API, SDK, webhooks, MCP, plugins)Offers ten official SDKs, an MCP server, and Agent Skills for AI agents S27 S62.S27 S62
Data ownership and exportUsers can export data before deleting instances S29.S29
Performance and reliability claimsEnterprise Edition provides fault-tolerant clusters across availability zones and distributed live queries S49.S49
Release activityThe engine has shipped 101 releases, with the latest v3.3.4, and major versions 1.0 and 3.0 released in 2023 and 2026 S1.S1
20

Measured infrastructure

Domain, certificate, and hosting signals, measured directly.

SignalFinding
Domain registered2016-04-11 — Name.com, Inc.
Domain expires2027-04-11
First archived2018-08-08 — web archive
TLS certificateLet's Encrypt, valid, expires 2026-12-25
Security headersHSTS, CSP, X-Content-Type-Options, X-Frame-Options, Referrer-Policy
Server headerVercel
Mail handled byaspmx.l.google.com, alt1.aspmx.l.google.com
Nameserversns-724.awsdns-26.net, ns-1456.awsdns-54.org
21

Technical site audit

A bounded multi-page crawl with page-level issues and URLs.

Scout — Bounded technical crawl

  • Pages crawled: 15 of 15 maximum
  • Technical health: 100/100
  • Critical issues: 0
  • Warnings: 0
  • Notices: 0

Issues

The bounded crawl did not detect title, description, H1, canonical, indexing, thin-content, image-alt, response-time, or duplicate-metadata issues.

Crawled pages

StatusTitleH1sWordsResponseURL
200The context and memory layer for AI agents \SurrealDB112111,352 ms
200One database, every data model \SurrealDB11339509 ms
200Features \SurrealDB1758367 ms
200SurrealQL \Database1575299 ms
200Technical deep-dive \SurrealDB11957517 ms
200Benchmarks \SurrealDB125861,047 ms
200SurrealDB Cloud \Fully managed, GB to PB196951 ms
200SurrealDB Studio \Your database and memory, visualised112031,191 ms
200Embedded and edge \Use cases \SurrealDB11091
200Integrations and ecosystem \SurrealDB1106080 ms
200Graph and vector \SurrealDB11100487 ms
200Realtime \SurrealDB11124346 ms
200Auth \SurrealDB11151581 ms
200Object storage \SurrealDB11077306 ms
200AI agents \Use cases \SurrealDB11131

This is a bounded Scout crawl. Core Web Vitals and Lighthouse scores are not claimed unless a dedicated performance audit is connected.

22

Search Console and Analytics

First-party search and behavioral data connection state.

Modeled acquisition channels

ChannelEstimated share
direct30.5%
search48.1%
search organic40.6%
search paid7.5%
social5.3%
social organic3.1%
social paid2.2%
referrals11.7%
paid referrals2.5%
mail0.7%
gen ai1.2%
affiliate0.0%
other0.0%

First-party connections

IntegrationStatusData available after connection
Google Search ConsoleNot connectedClicks, impressions, CTR, average position, queries, pages, countries, and devices
Google AnalyticsNot connectedOrganic sessions, engagement, landing pages, conversions, geography, and devices

No first-party Search Console or Analytics numbers are shown until the site owner authorizes the corresponding Google account. Scout traffic model values above are modeled estimates, not private analytics totals.

Limits and method

23

Limitations and open questions

Known constraints and missing evidence from the collected pages.

The collected pages do not name any competitors. Pricing for the Scale plan's included usage is not published S29. Enterprise licensing and support details are handled directly by the team rather than published S49. No independent review ratings or customer testimonials were collected; the About page names Samsung, Verizon, and Tencent as production users S1.

24

Sources, method, and limitations

Evidence inventory, collection method, provider use, and constraints.

This report is based on 15 collected pages from surrealdb.com, including the About page, documentation sections, and an authoritative pricing table from the pricing page. Static and browser rendering rendering were used; external proof search was enabled but only verified the existence of linked results, not their content. Pricing data was read on 2026-10-20 and may change. Claims are cited with source tokens S1–S39.

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