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Daytona vs Dgraph

Daytona logo

Daytona

Developer Tools

Infrastructure for spinning up secure, sub-second sandboxes to run AI-generated code

From
Free
Free plan
Yes
Visit DaytonaFull review
Dgraph logo

Dgraph

Databases

Apache 2.0 distributed graph database written in Go, maintained by Hypermode, queried through GraphQL or its own DQL language.

From
Free
Free plan
Yes
Visit DgraphFull review

The short version

  • Free plans on both; paid from $0.0504/mo and $39/mo.
  • Only Daytona lists sub-second sandbox creation; only Dgraph lists apache 2.0 licence.
  • Where Daytona falls short: pricing is purely usage-based with no flat monthly plan, which can make costs harder to predict for steady workloads.
  • Prices and features on this page were last checked on 13 November 2026.

Where they differ

Only the attributes on which Daytona and Dgraph actually diverge.

Attributes where Daytona and Dgraph differ
AttributeDaytonaDgraph
Pricing modelUsage-basedFreemium
PlatformsWeb, Linux, Windows, APILinux, macOS, Self-hosted, Web
CategoryDeveloper ToolsDatabases

Identical on both: starting price (Free), free tier (Yes).

Not yet recorded: founded for Daytona.

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Daytona

  • Sub-second sandbox creation
  • Per-second billing
  • GPU instances
  • Windows OS support
  • Enterprise BYOC

Only in Dgraph

  • Apache 2.0 licence
  • Generated GraphQL API
  • DQL query language
  • Predicate sharding
  • Raft replication
  • Distributed ACID transactions
  • Written in Go
  • Full-text and geo indexing

What people use each for

The jobs each tool is most often brought in to do.

Daytona

  • Running AI agent-generated code in a disposable, isolated sandboxnot Dgraph
  • Executing untrusted user code for a coding platformnot Dgraph
  • Running GPU workloads on demand without provisioning dedicated serversnot Dgraph
  • Testing Windows-specific code paths in a sandboxnot Dgraph

Dgraph

  • An application whose core data is a graph, such as permissions, social connections or product relationships, where the frontend already consumes GraphQLnot Daytona
  • A knowledge graph that outgrew a single machine and needs storage distributed across nodes without a per-core licence negotiationnot Daytona
  • Recommendation or fraud-detection features that traverse several hops at request time, where a relational join chain has become the bottlenecknot Daytona
  • Teams that want a graph database they can read, fork and self-host under a permissive licence rather than a source-available onenot Daytona

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Daytona

  • Pricing is purely usage-based with no flat monthly plan, which can make costs harder to predict for steady workloads
  • GPU instances are priced separately and can be significantly more expensive than standard compute for AI-heavy use cases
  • Enterprise features like SSO, audit logs, and BYOC are only available by contacting sales rather than self-serve

Dgraph

  • Sharding is by predicate, so a single very hot predicate lives entirely in one Raft group and cannot be split further; adding nodes does not relieve it and the fix is a data model change
  • Stewardship passed from Dgraph Labs to Hypermode after the original company stopped operating independently, so anyone building on it is betting on a second custodian rather than on the original team's roadmap
  • The GraphQL layer is generated and opinionated, so anything it does not express drops you into DQL, which is a second language your team must learn and which no other database speaks
  • The community is a fraction of Neo4j's, so operational answers, tuning experience, hiring and third-party tooling are all thinner, and unusual failure modes in a Zero and Alpha cluster leave you reading source rather than a forum
  • There is no portable graph standard to migrate to; Cypher, Gremlin and SPARQL are all different query models, so the schema and every query is a rewrite if you later leave, and that cost grows with the application

Pricing, plan by plan

Daytona

Free
  • Pay-as-you-goOn request
    • $0.0504 per vCPU/hour
    • $0.0162 per GiB memory/hour
    • $0.000108 per GiB storage/hour after 5 free GiB
  • Startup ProgramOn request
    • Up to $50,000 in free credits for qualifying startups
  • EnterpriseOn request
    • Custom usage limits
    • SSO
    • Audit logs

Dgraph

Free
  • CommunityFree
    • Native GraphQL
    • Graph queries
    • Full-text search
  • Cloud$39/mo
    • Managed service
    • Auto-scaling
    • Enterprise support

Which should you pick?

Choose Daytona if

  • You need sub-second sandbox creation.
  • You want to start without paying.
  • You work on Web, Linux, Windows, API.
  • You also want per-second billing.
Daytona review

Choose Dgraph if

  • You need apache 2.0 licence.
  • You want to start without paying.
  • You work on Linux, macOS, Self-hosted, Web.
  • You also want generated graphql api.
Dgraph review

Questions people ask

Is Daytona or Dgraph better?
Neither clearly leads. Daytona starts at Free and Dgraph at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Daytona or Dgraph?
Daytona starts at Free and Dgraph at Free.
Does Daytona or Dgraph run on more platforms?
Daytona runs on Web, Linux, Windows, API. Dgraph runs on Linux, macOS, Self-hosted, Web.
Can I use Daytona for free?
Both have a free tier, so you can try either at no cost before committing.
What is Daytona best used for?
Daytona is most often used for running ai agent-generated code in a disposable, isolated sandbox, executing untrusted user code for a coding platform, running gpu workloads on demand without provisioning dedicated servers, testing windows-specific code paths in a sandbox. Of those, running ai agent-generated code in a disposable, isolated sandbox and executing untrusted user code for a coding platform are not what Dgraph is typically brought in for.
What can Daytona do that Dgraph cannot?
Daytona covers Sub-second sandbox creation, Per-second billing, GPU instances, Windows OS support. Dgraph covers Apache 2.0 licence, Generated GraphQL API, DQL query language, Predicate sharding.

Answered from the vendors’ own pages

Daytona: How is Daytona usage metered?

Usage is billed per second across vCPU, memory, and storage consumed, with separate per-hour rates for GPU and Windows instances.

Source
Dgraph: Is Dgraph open source?

Yes. The current repository is Apache 2.0, which is a permissive OSI licence, and the project is at v25 under Hypermode's maintenance.

Daytona: Is there a free plan, and what are its limits?

There is no flat free plan, but new signups receive $200 in free compute credit with no credit card required to start.

Source
Dgraph: Is it really GraphQL?

It serves a generated GraphQL API, which is real GraphQL for clients. Its native language, DQL, resembles GraphQL syntactically but is Dgraph's own language and is not the GraphQL specification.

Daytona: Are discounts available for startups?

Yes, the Startup Program offers up to $50,000 in free credits for qualifying companies.

Source
Dgraph: How does it compare to Neo4j?

Neo4j has the larger ecosystem, Cypher, and far more operational precedent. Dgraph distributes storage across nodes by default and gives you a GraphQL endpoint without writing resolvers. The choice usually turns on whether you need horizontal scale and a GraphQL surface more than you need ecosystem depth.

Dgraph: What does a production cluster look like?

At minimum a set of Zero nodes for coordination and a replicated set of Alpha nodes for data, typically three of each for fault tolerance, which is a meaningfully larger operational footprint than a single graph server.

Dgraph: Who maintains it now?

Hypermode. Dgraph Labs, the original company, no longer operates it, and that change of custodian is the main non-technical risk to weigh.

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