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Databases · head to head

Apache Pinot vs Dgraph

Apache Pinot logo

Apache Pinot

Databases

Real-time distributed OLAP datastore for analytics

From
Free
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

  • Each has a real cost: Apache Pinot self-hosted and distributed, so running it means operating a cluster rather than consuming a service; 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: Apache Pinot covers Real-time Analytics, Dgraph covers Apache 2.0 licence.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Apache Pinot and Dgraph actually diverge.

Attributes where Apache Pinot and Dgraph differ
AttributeApache PinotDgraph
Pricing modelopen-sourcefreemium
PlatformsLinux, Docker, KubernetesLinux, Mac, Docker, Web
Founded19992016

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 Apache Pinot

  • Real-time Analytics
  • Column-oriented
  • Distributed Processing
  • SQL Support
  • Pluggable Indexing
  • Star-tree Index
  • Upsert Support
  • Kafka

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.

Apache Pinot

  • Sub-second analytics queries on freshly ingested datanot Dgraph
  • User-facing dashboards inside a productnot Dgraph
  • Real-time metrics at high ingest ratesnot Dgraph
  • Petabyte-scale analytics as run at LinkedIn and Ubernot Dgraph

Dgraph

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

Where each one falls short

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

Apache Pinot

  • Self-hosted and distributed, so running it means operating a cluster rather than consuming a service
  • Managed hosting comes from third parties such as StarTree rather than from the project
  • Built for user-facing real-time OLAP, so it is not a general purpose database

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

Apache Pinot

Free
  • Open SourceFree
    • Real-time analytics
    • SQL queries
    • Horizontal scaling

Dgraph

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

Which should you pick?

Choose Apache Pinot if

  • You need real-time analytics.
  • You want to start without paying.
  • You work on Linux, Docker, Kubernetes.
  • You also want column-oriented.
Apache Pinot 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 Apache Pinot or Dgraph better?
Neither clearly leads. Apache Pinot 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, Apache Pinot or Dgraph?
Apache Pinot starts at Free and Dgraph at Free.
Does Apache Pinot or Dgraph run on more platforms?
Apache Pinot runs on Linux, Docker, Kubernetes. Dgraph runs on Linux, Mac, Docker, Web.
Can I use Apache Pinot for free?
Both have a free tier, so you can try either at no cost before committing.
What is Apache Pinot best used for?
Apache Pinot is most often used for sub-second analytics queries on freshly ingested data, user-facing dashboards inside a product, real-time metrics at high ingest rates, petabyte-scale analytics as run at linkedin and uber. Of those, sub-second analytics queries on freshly ingested data and user-facing dashboards inside a product are not what Dgraph is typically brought in for.
What can Apache Pinot do that Dgraph cannot?
Apache Pinot covers Real-time Analytics, Column-oriented, Distributed Processing, SQL Support. Dgraph covers Apache 2.0 licence, Generated GraphQL API, DQL query language, Predicate sharding.

Answered from the vendors’ own pages

Apache Pinot: How much does Apache Pinot cost?

Apache Pinot is free and open-source. It is provided under the Apache License, which allows free use, modification, and distribution.

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.

Apache Pinot: Is Apache Pinot free for commercial use?

Yes. Apache Pinot is licensed under the Apache License, which explicitly permits commercial use at no cost.

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.

Apache Pinot: Can I run Apache Pinot locally or with Docker?

Yes. Apache Pinot offers a Docker quickstart and free downloads of the latest version (1.5.1 at the time of the page). You are responsible for hosting and infrastructure.

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.

Apache Pinot: Are there restrictions on how I can use Apache Pinot?

The Apache License permits unrestricted use, but requires retention of license notices and statements. No usage limits or feature restrictions are enforced.

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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