Dgraph is a focused, fully open-source graph database with a native GraphQL API and no commercial pricing to evaluate, while SurrealDB is a multi-model…
Best for Dgraph: Teams that specifically need a graph database with native GraphQL access, are comfortable self-hosting under Apache 2.0, and don't require a vendor-managed cloud or published SLA.
Best for SurrealDB: Teams that want to consolidate document, graph, vector, and relational workloads into one engine, need AI/RAG-oriented features like agent memory and knowledge graphs, and want the option of an hourly-billed managed cloud or a custom Enterprise plan with SSO and audit logging.
At a Glance
Dgraph
SurrealDB
Primary category
Databases
Databases
Rating
Not documented
Not documented
Pricing model
Free/Open Source with paid Cloud tiers
freemium
Starting price
Free
Free
Free plan
Yes
Yes
Free trial
Not documented
Not documented
Platforms
Not documented
Not documented
Team collaboration
Not documented
Not documented
AI features
Not documented
Yes
Public API
Yes
Yes
Key Differences
Data model scope
Dgraph: Purpose-built graph database with a native GraphQL API, property-graph queries, full-text search, regex matching, and geo search.
SurrealDB: Multi-model engine unifying document, graph, vector, time-series, and relational data through a single query language, SurrealQL.
Teams with a single, well-defined graph workload get a lean fit from Dgraph, while teams juggling several data shapes can avoid standing up multiple specialized databases with SurrealDB.
Commercial backing and managed hosting
Dgraph: No published pricing and no confirmed active managed cloud offering; project ownership has moved from Dgraph Labs to Hypermode to Istari Digital.
SurrealDB: Publishes an hourly-priced Start (free forever, 1 instance/1GB) and Scale plan, plus a custom Enterprise tier with SSO, audit logging, and FIPS-compliant cryptography.
Organizations that need a vendor support contract, SLA, or managed hosting option can't currently rely on Dgraph's commercial status, whereas SurrealDB offers a documented path from free to enterprise.
AI and agent-memory tooling
Dgraph: No AI or agent-memory features are documented.
SurrealDB: Includes Spectron, a built-in agent memory system with entity extraction and knowledge graph construction, plus hybrid RAG and vector search.
Teams building AI agents or RAG pipelines get purpose-built primitives from SurrealDB that Dgraph does not offer.
Licensing and deployment model
Dgraph: Apache 2.0 open source, self-hosted only, with no company or pricing page to evaluate.
SurrealDB: Freemium model combining a free self-hosted-capable Start tier with paid hourly cloud plans and a custom self-hosted Enterprise option.
Dgraph is a pure self-hosting decision; SurrealDB lets teams start free, move to paid cloud, or self-host at the Enterprise tier as needs grow.
Starting price reflects the lowest paid tier, not the full cost for every team size or usage level.
Dgraph
Open Source (self-hosted) — Free N/A
Dgraph Cloud Free — Free N/A
Dgraph Cloud Shared — $39.99/month per backend Monthly
Dgraph Cloud Dedicated — From $199/month Monthly
SurrealDB
Self-Hosted — Free N/A
Start (Cloud) — Free instance, then from $0.021/hr usage-based
Scale (Cloud) — From $0.192/node/hr usage-based
Enterprise — Custom custom
Pros & Cons
Dgraph
Pros
Free and open-source core with no licensing cost for self-hosting
Natively distributed architecture scales linearly with added nodes
First-class GraphQL support simplifies application development
Strong open-source community with an active GitHub project
Cons
Ownership changes (Hypermode acquisition in 2023, Istari Digital in 2025) create uncertainty about long-term commercial roadmap
Smaller ecosystem and talent pool compared to Neo4j
Managed Cloud pricing can add up for high-data-transfer workloads
Steeper learning curve for teams unfamiliar with graph query languages
SurrealDB
Pros
Replaces multiple specialized databases with a single multi-model engine
Flexible deployment options from embedded to fully managed cloud
Free tier and free self-hosted use for prototyping and small projects
Well-funded with backing from established venture investors
Native vector search suited to modern AI application needs
Cons
Newer database with a shorter production track record than established systems
Some advanced cloud features like branching and forking are still rolling out
SurrealQL requires learning a new query language distinct from standard SQL
Source-available licensing terms may require review for some enterprise use cases
Smaller ecosystem of third-party tools and integrations compared to legacy databases
Use Cases
Choose Dgraph: Teams that specifically need a graph database with native GraphQL access, are comfortable self-hosting under Apache 2.0, and don't require a vendor-managed cloud or published SLA.
Choose SurrealDB: Teams that want to consolidate document, graph, vector, and relational workloads into one engine, need AI/RAG-oriented features like agent memory and knowledge graphs, and want the option of an hourly-billed managed cloud or a custom Enterprise plan with SSO and audit logging.
Need both: Organizations already running a graph-only workload on Dgraph that are separately evaluating SurrealDB for a new AI/RAG or multi-model project may end up operating both rather than migrating existing graph data.
Dgraph
Knowledge graph applications — Teams model deeply interconnected entities and relationships that are cumbersome to query with SQL joins.
Recommendation and social graph systems — Applications that need fast traversal of user, content, and interaction relationships use Dgraph for low-latency graph queries.
Managed graph database hosting — Teams that want graph database capability without operating infrastructure use Dgraph Cloud's shared or dedicated tiers.
SurrealDB
Unified data layer for serverless apps — Startups use SurrealDB as a single database for document, relational, and graph data in serverless and JAMstack applications.
AI and retrieval-augmented generation — AI teams combine vector search with relational and graph data in one engine for RAG and semantic search pipelines.
Database consolidation for enterprises — Enterprises use SurrealDB to reduce the number of specialized databases they operate and maintain.
Frequently Asked Questions
Is Dgraph free to use?
Yes, Dgraph is released under the Apache 2.0 open-source license and can be self-hosted at no cost, though no commercial pricing or managed cloud is currently documented.
Does SurrealDB have a free tier?
Yes, the Start plan includes one free instance and 1GB of storage forever, plus a no-signup sandbox.
Does Dgraph support GraphQL?
Yes, it offers a native GraphQL API in addition to direct property-graph database access.
What data models does SurrealDB support?
It unifies document, graph, vector, time-series, and relational data models in one engine with ACID transactions.
Who owns Dgraph now?
Dgraph originated at Dgraph Labs, which was acquired by Hypermode, later acquired by Istari Digital; the open-source project continues under this lineage.
Is there a SurrealDB Enterprise plan?
Yes, it offers self-hosted deployment, audit logging, SSO, and SLA-backed uptime, with custom pricing.