Databases · head to head
Amazon Aurora vs Dgraph

Amazon Aurora
Databases
MySQL and PostgreSQL-compatible relational database built for the cloud
- From
- Free
- Rated
- -

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
- -
The short version
- Each has a real cost: Amazon Aurora aurora requires AWS ecosystem knowledge and integration with other AWS services; 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: Amazon Aurora covers MySQL/PostgreSQL Compatible, 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 Amazon Aurora and Dgraph actually diverge.
| Attribute | Amazon Aurora | Dgraph |
|---|---|---|
| Pricing model | usage-based | freemium |
| Platforms | AWS Cloud | Linux, Mac, Docker, Web |
| Founded | 2006 | 2016 |
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 Amazon Aurora
- MySQL/PostgreSQL Compatible
- 5x MySQL Performance
- Auto-scaling Storage
- Global Database
- Serverless v2
- Multi-master
- Fault Tolerant
- AWS Lambda
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.
Amazon Aurora
- Transaction processingnot Dgraph
- Data storagenot Dgraph
- Application backendnot Dgraph
- Reportingnot Dgraph
- Data analyticsnot Dgraph
Dgraph
- An application whose core data is a graph, such as permissions, social connections or product relationships, where the frontend already consumes GraphQLnot Amazon Aurora
- A knowledge graph that outgrew a single machine and needs storage distributed across nodes without a per-core licence negotiationnot Amazon Aurora
- Recommendation or fraud-detection features that traverse several hops at request time, where a relational join chain has become the bottlenecknot Amazon Aurora
- Teams that want a graph database they can read, fork and self-host under a permissive licence rather than a source-available onenot Amazon Aurora
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Amazon Aurora
- Aurora requires AWS ecosystem knowledge and integration with other AWS services
- Pricing can become expensive with high-traffic applications using many read replicas
- Limited support for non-relational data types compared to NoSQL alternatives
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
Amazon Aurora
Free- Serverless v2$0.12/hour
- Auto-scaling
- Pay per ACU
- Instant scaling
- Provisioned$29/month
- Dedicated instances
- Predictable performance
- Reserved capacity
Dgraph
Free- CommunityFree
- Native GraphQL
- Graph queries
- Full-text search
- Cloud$39/month
- Managed service
- Auto-scaling
- Enterprise support
Which should you pick?
Choose Amazon Aurora if
- You need mysql/postgresql compatible.
- You want to start without paying.
- You work on AWS Cloud.
- You also want 5x mysql performance.
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.
Questions people ask
- Is Amazon Aurora or Dgraph better?
- Neither clearly leads. Amazon Aurora 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, Amazon Aurora or Dgraph?
- Amazon Aurora starts at Free and Dgraph at Free.
- Does Amazon Aurora or Dgraph run on more platforms?
- Amazon Aurora runs on AWS Cloud. Dgraph runs on Linux, Mac, Docker, Web.
- Can I use Amazon Aurora for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Amazon Aurora best used for?
- Amazon Aurora is most often used for transaction processing, data storage, application backend, reporting. Of those, transaction processing and data storage are not what Dgraph is typically brought in for.
- What can Amazon Aurora do that Dgraph cannot?
- Amazon Aurora covers MySQL/PostgreSQL Compatible, 5x MySQL Performance, Auto-scaling Storage, Global Database. Dgraph covers Apache 2.0 licence, Generated GraphQL API, DQL query language, Predicate sharding.
Answered from the vendors’ own pages
Amazon Aurora: Is Amazon Aurora compatible with MySQL and PostgreSQL?
Yes, Amazon Aurora offers MySQL and PostgreSQL compatibility with full compatibility to their open-source counterparts, allowing you to migrate existing databases with standard tools.
SourceDgraph: 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.
Amazon Aurora: What uptime SLA does Amazon Aurora provide?
Aurora is designed for up to 99.99% single-region uptime and 99.999% multi-region uptime with automatic failover.
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.
Amazon Aurora: How much does Amazon Aurora cost?
Aurora uses serverless, usage-based pricing where you pay only for consumed capacity. Typical pricing ranges from $50-70 per month for minimal setups to $400-600 per month for small production clusters.
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.
Amazon Aurora: Can Amazon Aurora scale automatically?
Yes, Aurora automatically scales to match workload demands without performance degradation, supporting both read and write scaling.
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.
Amazon Aurora: How many read replicas does Aurora support?
Aurora supports up to 15 low-latency read replicas for distributing read traffic across your application.
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
More on Amazon Aurora
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