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Databases · head to head

Dgraph vs Readyset

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
Rated
-
Full reviewWebsite
Readyset logo

Readyset

Databases

Database caching and optimization that reduces infrastructure costs 30-70%

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: 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.; Readyset pricing requires contacting sales team, making cost planning difficult
  • They diverge on capability: Dgraph covers Apache 2.0 licence, Readyset covers Automatic Query Optimization.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Dgraph and Readyset actually diverge.

Attributes where Dgraph and Readyset differ
AttributeDgraphReadyset
Pricing modelfreemiumMonthly or annual subscription based on cache size
PlatformsLinux, Mac, Docker, WebCloud, Self-Hosted
Founded2016Unknown

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Databases).

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 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

Only in Readyset

  • Automatic Query Optimization
  • SQL-Level Caching
  • Live Incremental Updates
  • Zero-Touch Integration
  • Query Interception
  • AI Query Protection

What people use each for

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

Dgraph

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

Readyset

  • Reducing database costs for AI workloads with unpredictable query patternsnot Dgraph
  • Improving read performance for frequently accessed data without hardware upgradesnot Dgraph
  • Protecting databases from performance degradation caused by agentic queriesnot Dgraph
  • Scaling read-heavy applications without database scaling costsnot Dgraph

Where each one falls short

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

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.

Readyset

  • Pricing requires contacting sales team, making cost planning difficult
  • Specific pricing tiers not disclosed publicly
  • Requires cache size estimation for cost calculation
  • Limited to read query caching, does not address write performance

Pricing, plan by plan

Dgraph

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

Readyset

Free
  • CommunityFree
    • Free tier for evaluation
    • 7-day trial available
  • Readyset CloudFree
    • Fully-managed AWS deployment
    • High availability
    • VPC peering support
  • Readyset PrivateFree
    • Self-hosted on your servers
    • Complete control
    • Custom deployment

Which should you pick?

Choose Dgraph if

  • You need apache 2.0 licence.
  • You want to start without paying.
  • You work on Linux, Mac, Docker, Web.
  • You also want generated graphql api.
Dgraph review

Choose Readyset if

  • You need automatic query optimization.
  • You want to start without paying.
  • You work on Cloud, Self-Hosted.
  • You also want sql-level caching.
Readyset review

Questions people ask

Is Dgraph or Readyset better?
Neither clearly leads. Dgraph starts at Free and Readyset at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Dgraph or Readyset?
Dgraph starts at Free and Readyset at Free.
Does Dgraph or Readyset run on more platforms?
Dgraph runs on Linux, Mac, Docker, Web. Readyset runs on Cloud, Self-Hosted.
Can I use Dgraph for free?
Both have a free tier, so you can try either at no cost before committing.
What is Dgraph best used for?
Dgraph is most often used for an application whose core data is a graph, such as permissions, social connections or product relationships, where the frontend already consumes graphql, a knowledge graph that outgrew a single machine and needs storage distributed across nodes without a per-core licence negotiation, recommendation or fraud-detection features that traverse several hops at request time, where a relational join chain has become the bottleneck, teams that want a graph database they can read, fork and self-host under a permissive licence rather than a source-available one. Of those, an application whose core data is a graph, such as permissions, social connections or product relationships, where the frontend already consumes graphql and a knowledge graph that outgrew a single machine and needs storage distributed across nodes without a per-core licence negotiation are not what Readyset is typically brought in for.
What can Dgraph do that Readyset cannot?
Dgraph covers Apache 2.0 licence, Generated GraphQL API, DQL query language, Predicate sharding. Readyset covers Automatic Query Optimization, SQL-Level Caching, Live Incremental Updates, Zero-Touch Integration.

Answered from the vendors’ own pages

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.

Readyset: Do I need to change my application code?

No, Readyset integrates transparently through query interception with zero code changes or schema modifications required.

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.

Readyset: Is there a free trial?

Yes, Readyset offers a free 7-day trial that lets you test different cache sizes before committing to a paid plan.

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.

Readyset: How does Readyset pricing work?

Readyset is available as a monthly or annual subscription charged based on the size of cache you need. Contact [email protected] for specific pricing.

Source
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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