Databases · head to head
Dgraph vs Vespa

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
- -

Vespa
Databases
Distributed AI search platform for retrieval, ranking, and inference
- From
- Free
- Rated
- -
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.; Vespa pricing not publicly listed, requires contacting sales
- They diverge on capability: Dgraph covers Apache 2.0 licence, Vespa covers Vector search.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which Dgraph and Vespa actually diverge.
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 Vespa
- Vector search
- Text and structured search
- Machine-learned ranking
- Real-time serving
- SQL interface
- Automatic scaling
- Open-source
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 Vespa
- A knowledge graph that outgrew a single machine and needs storage distributed across nodes without a per-core licence negotiationnot Vespa
- Recommendation or fraud-detection features that traverse several hops at request time, where a relational join chain has become the bottlenecknot Vespa
- Teams that want a graph database they can read, fork and self-host under a permissive licence rather than a source-available onenot Vespa
Vespa
- Build RAG systems with semantic search over documentsnot Dgraph
- Power e-commerce search with ML rankingnot Dgraph
- Create recommendation engines for personalizationnot Dgraph
- Implement real-time search for news or feedsnot Dgraph
- Deploy private semantic search over sensitive datanot 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.
Vespa
- Pricing not publicly listed, requires contacting sales
- Steeper learning curve compared to simpler search tools
- Operational complexity for self-hosted deployments
- Smaller ecosystem compared to cloud-native alternatives
Pricing, plan by plan
Dgraph
Free- CommunityFree
- Native GraphQL
- Graph queries
- Full-text search
- Cloud$39/month
- Managed service
- Auto-scaling
- Enterprise support
Vespa
FreeNo published plan breakdown. See the Vespa review.
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.
Choose Vespa if
- You need vector search.
- You want to start without paying.
- You work on Cloud, Self-hosted.
- You also want text and structured search.
Questions people ask
- Is Dgraph or Vespa better?
- Neither clearly leads. Dgraph starts at Free and Vespa at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Dgraph or Vespa?
- Dgraph starts at Free and Vespa at Free.
- Does Dgraph or Vespa run on more platforms?
- Dgraph runs on Linux, Mac, Docker, Web. Vespa 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 Vespa is typically brought in for.
- What can Dgraph do that Vespa cannot?
- Dgraph covers Apache 2.0 licence, Generated GraphQL API, DQL query language, Predicate sharding. Vespa covers Vector search, Text and structured search, Machine-learned ranking, Real-time serving.
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.
Vespa: Is Vespa open-source?
Yes, Vespa is open-source under the Apache 2.0 license. The code is available on GitHub, and you can self-host or use the managed cloud service.
SourceDgraph: 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.
Vespa: What latency can Vespa achieve?
Vespa is designed for sub-100 millisecond latencies with thousands of queries per second, suitable for real-time search and recommendation applications.
SourceDgraph: 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.
Vespa: Does Vespa support vector search?
Yes, Vespa provides native vector search capabilities alongside text, structured data, and tensor operations for building comprehensive search and AI applications.
SourceDgraph: 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.
Vespa: What is the pricing model for Vespa Cloud?
Vespa Cloud pricing is not publicly listed and requires contacting their sales team to discuss your specific use case and scale requirements.
SourceDgraph: 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.
Related pages
Other head to heads
- Dgraph vs Cockroach Labs
- Dgraph vs Airtable
- Dgraph vs PostgreSQL
- Dgraph vs Amazon Aurora
- Dgraph vs Neo4j
- Dgraph vs ArangoDB
- Dgraph vs Elasticsearch
- Dgraph vs Couchbase
- Dgraph vs Cassandra
- Dgraph vs FaunaDB
- Dgraph vs Firebase Realtime Database
- Dgraph vs RavenDB
- Dgraph vs Convex
- Dgraph vs Dragonfly
- Dgraph vs Dremio
- Dgraph vs Fivetran HVR
- Dgraph vs Grist
- Dgraph vs IBM Db2
- Dgraph vs Zilliz
- Dgraph vs Meilisearch
- Dgraph vs Typesense
- Dgraph vs SurrealDB
- Dgraph vs OpenSearch
- Dgraph vs Apache Solr
- Dgraph vs Marqo
- Dgraph vs Chroma
- Dgraph vs Qdrant
- Dgraph vs Materialize
- Dgraph vs Estuary
- Dgraph vs Instaclustr
- Dgraph vs Knack
- Dgraph vs LanceDB
- Vespa vs Cockroach Labs
- Vespa vs Airtable
- Vespa vs PostgreSQL
- Vespa vs Amazon Aurora
- Vespa vs Neo4j
- Vespa vs ArangoDB
- Vespa vs Elasticsearch
- Vespa vs Couchbase
- Vespa vs Cassandra
- Vespa vs FaunaDB
- Vespa vs Firebase Realtime Database
- Vespa vs RavenDB
- Vespa vs Convex
- Vespa vs Dragonfly
- Vespa vs Dremio
- Vespa vs Fivetran HVR
- Vespa vs Grist
- Vespa vs IBM Db2
- Vespa vs Zilliz
- Vespa vs Meilisearch
- Vespa vs Typesense
- Vespa vs SurrealDB
- Vespa vs OpenSearch
- Vespa vs Apache Solr
- Vespa vs Marqo
- Vespa vs Chroma
- Vespa vs Qdrant
- Vespa vs Materialize
- Vespa vs Estuary
- Vespa vs Instaclustr
- Vespa vs Knack
- Vespa vs LanceDB
