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Databases · head to head

Dgraph vs NATS

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
NATS logo

NATS

Databases

High-performance messaging system for cloud-native applications

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.; NATS core NATS has no persistence at all, so messages are lost if no subscriber is listening
  • They diverge on capability: Dgraph covers Apache 2.0 licence, NATS covers Very low latency.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Dgraph and NATS actually diverge.

Attributes where Dgraph and NATS differ
AttributeDgraphNATS
Pricing modelfreemiumOpen source, no licence fee
PlatformsLinux, Mac, Docker, WebLinux, macOS, Windows, Docker, Kubernetes
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 NATS

  • Very low latency
  • JetStream
  • Single binary
  • Request-reply

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 NATS
  • A knowledge graph that outgrew a single machine and needs storage distributed across nodes without a per-core licence negotiationnot NATS
  • Recommendation or fraud-detection features that traverse several hops at request time, where a relational join chain has become the bottlenecknot NATS
  • Teams that want a graph database they can read, fork and self-host under a permissive licence rather than a source-available onenot NATS

NATS

  • Service-to-service messaging where latency is the binding constraintnot Dgraph
  • Edge and IoT messaging where a lightweight broker mattersnot Dgraph
  • Replacing a heavier broker when the workload does not need its guaranteesnot 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.

NATS

  • Core NATS has no persistence at all, so messages are lost if no subscriber is listening
  • JetStream adds the durability but also the operational complexity NATS is chosen to avoid
  • A much smaller ecosystem than Kafka or RabbitMQ, with fewer connectors and integrations
  • Fewer people know it, so hiring and existing organisational knowledge favour the alternatives

Pricing, plan by plan

Dgraph

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

NATS

Free
  • NATSFree
    • Full functionality
    • No usage limits
    • Community support

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 NATS if

  • You need very low latency.
  • You want to start without paying.
  • You work on Linux, macOS, Windows, Docker, Kubernetes.
  • You also want jetstream.
NATS review

Questions people ask

Is Dgraph or NATS better?
Neither clearly leads. Dgraph starts at Free and NATS at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Dgraph or NATS?
Dgraph starts at Free and NATS at Free.
Does Dgraph or NATS run on more platforms?
Dgraph runs on Linux, Mac, Docker, Web. NATS runs on Linux, macOS, Windows, Docker, Kubernetes.
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 NATS is typically brought in for.
What can Dgraph do that NATS cannot?
Dgraph covers Apache 2.0 licence, Generated GraphQL API, DQL query language, Predicate sharding. NATS covers Very low latency, JetStream, Single binary, Request-reply.

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.

NATS: Is NATS free?

Yes, open source and CNCF-graduated. Synadia sells a managed service.

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.

NATS: Does NATS persist messages?

Core NATS does not — it is fire-and-forget. JetStream adds persistence, streaming and replay when you need them.

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.

NATS: NATS or Kafka?

NATS is far lighter and lower latency, and much simpler to run. Kafka is the answer when you need a durable replayable log and a large connector ecosystem.

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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