Databases · head to head
Dgraph vs Estuary
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
- -
Estuary
Databases
Real-time data integration combining streaming, CDC, and batch
- 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.; Estuary per-GB pricing adds up quickly for high-volume scenarios
- They diverge on capability: Dgraph covers Apache 2.0 licence, Estuary covers Real-time data delivery.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which Dgraph and Estuary 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 Estuary
- Real-time data delivery
- Change data capture
- Batch processing
- Data transformation
- Pre-built connectors
- Multiple deployments
- RBAC and monitoring
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 Estuary
- A knowledge graph that outgrew a single machine and needs storage distributed across nodes without a per-core licence negotiationnot Estuary
- Recommendation or fraud-detection features that traverse several hops at request time, where a relational join chain has become the bottlenecknot Estuary
- Teams that want a graph database they can read, fork and self-host under a permissive licence rather than a source-available onenot Estuary
Estuary
- Real-time data replication to data warehousesnot Dgraph
- Change data capture from operational databasesnot Dgraph
- Feeding analytics and BI systems with fresh datanot Dgraph
- Powering real-time AI and ML data pipelinesnot 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.
Estuary
- Per-GB pricing adds up quickly for high-volume scenarios
- No transparent per-connector volume discounts below 6 connectors
- Limited to data movement; transformation capabilities are basic
- BYOC and private deployment requires enterprise plan
- Smaller ecosystem compared to established alternatives
Pricing, plan by plan
Dgraph
Free- CommunityFree
- Native GraphQL
- Graph queries
- Full-text search
- Cloud$39/month
- Managed service
- Auto-scaling
- Enterprise support
Estuary
Free- DeveloperFree
- 10 GB per month
- 2 connector instances maximum
- No credit card required
- Cloud$0.5/GB
- $0.50 per GB of data moved
- $100 per connector monthly (6+ connectors $50 each)
- 200+ connectors
- Enterprise$null/custom
- Volume-based discounts
- SOC 2 and HIPAA compliance
- SSO authentication
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 Estuary if
- You need real-time data delivery.
- You want to start without paying.
- You work on Cloud, Private Cloud, BYOC.
- You also want change data capture.
Questions people ask
- Is Dgraph or Estuary better?
- Neither clearly leads. Dgraph starts at Free and Estuary at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Dgraph or Estuary?
- Dgraph starts at Free and Estuary at Free.
- Does Dgraph or Estuary run on more platforms?
- Dgraph runs on Linux, Mac, Docker, Web. Estuary runs on Cloud, Private Cloud, BYOC.
- 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 Estuary is typically brought in for.
- What can Dgraph do that Estuary cannot?
- Dgraph covers Apache 2.0 licence, Generated GraphQL API, DQL query language, Predicate sharding. Estuary covers Real-time data delivery, Change data capture, Batch processing, Data transformation.
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.
Estuary: What is included in the free Developer plan?
Developer plan ($0/month) includes 10 GB of data per month and up to 2 connector instances, no credit card required.
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.
Estuary: How is data pricing calculated on Cloud plan?
Cloud plan charges $0.50 per GB of data moved plus $100/month per connector for the first 6 connectors, then $50/month for additional connectors.
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.
Estuary: What discount is available when adding 6+ connectors?
When using 6 or more connectors, the per-connector cost drops to $50/month from $100/month, saving $50 per additional connector.
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.
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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