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Databases · head to head

Canary Labs vs Dgraph

Canary Labs logo

Canary Labs

Databases

Industrial process historian with published per-tag pricing and no client licence fees

From
$3000/year
Rated
-
Full reviewWebsite
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

The short version

  • Only Dgraph has a free tier, so it costs nothing to try first.
  • Each has a real cost: Canary Labs pricing steps by tag band rather than actual tags, so a site sitting just above a threshold pays the next band in full; growth from 3,400 to 3,600 tags is a licence purchase, not a rounding error.; 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.
  • They diverge on capability: Canary Labs covers Loss-less compression, Dgraph covers Apache 2.0 licence.
  • Prices and features above were last checked on 1 September 2026.

Where they differ

Only the attributes on which Canary Labs and Dgraph actually diverge.

Attributes where Canary Labs and Dgraph differ
AttributeCanary LabsDgraph
Starting price$3000/yearFree
Pricing modelPer tag band per yearfreemium
Free tierNoYes
PlatformsWindows, WebLinux, Mac, Docker, Web
FoundedUnknown2016

Identical on both: 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 Canary Labs

  • Loss-less compression
  • Unlimited clients
  • Store and forward
  • Views service
  • Sparkplug B
  • Calculation engine
  • Axiom
  • ODBC and REST

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.

Canary Labs

  • A manufacturer that needs a compliant historian but cannot justify a PI System enterprise agreementnot Dgraph
  • A water utility replacing SCADA-embedded logging with a historian that survives the next SCADA replacementnot Dgraph
  • An Ignition site that wants long-term storage and trending without paying per-client for dashboardsnot Dgraph
  • A plant with regulatory data-retention obligations where swinging-door compression would not survive an auditnot Dgraph

Dgraph

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

Where each one falls short

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

Canary Labs

  • Pricing steps by tag band rather than actual tags, so a site sitting just above a threshold pays the next band in full; growth from 3,400 to 3,600 tags is a licence purchase, not a rounding error.
  • CustomerCare at 18 percent of licence cost is effectively mandatory on perpetual licences because lapsing it removes upgrades, so the perpetual option is not really a one-time cost.
  • The storage format is proprietary; getting data out at volume means the ODBC connector, an additional 2,500 USD one-time or 1,000 USD a year, or writing against the REST API.
  • Canary is a small vendor with a limited partner network outside North America, so support coverage and integrator availability in Europe and Asia are thinner than for AVEVA or Ignition.
  • It is a Windows-only server product with no Linux or container deployment, which complicates placing collectors in modern edge estates.

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

Canary Labs

$3000/year
  • Subscription, 3,500 tags$3000/year
    • Unlimited Axiom clients
    • Unlimited Excel clients
    • Support and upgrades included
  • Perpetual, 3,500 tags$8730/one-time
    • 7,400 USD licence plus 1,330 USD first-year CustomerCare
    • CustomerCare renews at 18 percent of licence cost per year
    • Unlimited clients
  • Private cloud, 3,500 tags$12320/year
    • Hosted by Canary
    • 1,500 USD one-time setup fee per system
    • Scales to around 58,684 USD per year at 60,000 tags
  • Enterprise unlimited$undefined/year
    • Unlimited tags
    • Negotiated licensing terms
    • Quoted pricing

Dgraph

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

Which should you pick?

Choose Canary Labs if

  • You need loss-less compression.
  • You work on Windows, Web.
  • You also want unlimited clients.
Canary Labs review

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

Questions people ask

Is Canary Labs or Dgraph better?
Neither clearly leads. Canary Labs starts at $3000/year and Dgraph at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Canary Labs or Dgraph?
Dgraph has a free tier; the other does not. Paid plans start at $3000/year for Canary Labs and Free for Dgraph.
Does Canary Labs or Dgraph run on more platforms?
Canary Labs runs on Windows, Web. Dgraph runs on Linux, Mac, Docker, Web.
Can I use Dgraph for free?
Yes. Dgraph has a free tier, so you can try it without paying. Canary Labs starts at $3000/year.
What is Canary Labs best used for?
Canary Labs is most often used for a manufacturer that needs a compliant historian but cannot justify a pi system enterprise agreement, a water utility replacing scada-embedded logging with a historian that survives the next scada replacement, an ignition site that wants long-term storage and trending without paying per-client for dashboards, a plant with regulatory data-retention obligations where swinging-door compression would not survive an audit. Of those, a manufacturer that needs a compliant historian but cannot justify a pi system enterprise agreement and a water utility replacing scada-embedded logging with a historian that survives the next scada replacement are not what Dgraph is typically brought in for.
What can Canary Labs do that Dgraph cannot?
Canary Labs covers Loss-less compression, Unlimited clients, Store and forward, Views service. Dgraph covers Apache 2.0 licence, Generated GraphQL API, DQL query language, Predicate sharding.

Answered from the vendors’ own pages

Canary Labs: What does Canary cost?

8,730 USD for a 3,500 tag perpetual system including first-year CustomerCare, or 3,000 USD a year on subscription.

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.

Canary Labs: Are client licences extra?

No. Unlimited Axiom browser clients and unlimited Excel clients are included on every tier.

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.

Canary Labs: Is perpetual cheaper than subscription?

Canary states perpetual pays off after roughly three years, and after that you still pay 18 percent CustomerCare annually.

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.

Canary Labs: Does it use lossy compression?

No. Canary stores every collected value rather than approximating the trend, which matters for regulated data retention.

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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