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Dgraph vs Tigergraph

Which is the Best Graph Database?

Updated in Feb 2021



Native GraphQL Support


Only DB to natively support GraphQL


Distributed ACID Transactions

Supported and Jepsen tested.
  • Only single server ACID transactions, not distributed.
  • You cannot update the graph. Distributed queries currently (as of v2.1) can only read the graph data.
  • Reference

Horizontally Scalable

Dgraph scales vertically and horizontally with no downtime.
  • To go from a non-HA cluster to an HA-cluster, the database must be cleared and shut down first before adding new nodes.
  • Reference 1
  • Reference 2

Distributed Graph database



Consistent Replication

Synchronous replication across replicas (reference) Strong consistency

Linearizable Reads

Strong (sequential) consistency across clients

Open Source

  • Yes, Apache 2.0.
  • Proprietary code base is source-available.
  • GitHub


Tested for correctness, fault
tolerance and durability

Dgraph is the only graph database that went through Jepsen test not just once, but twice. Not Jepsen tested.

Suitability as a primary database to
build apps/data platform on

Yes, Dgraph is a general-purpose database. Read more on Dgraph case studies Built for **specific"" applications.

Query Language(s)


Multiple language drivers

C++, Java


HTTP/HTTPS, gRPC, Protocol Buffers (reference) HTTP/HTTPS


  • Using BulkLoader or LiveLoader, Dgraph can read the data as is with no modification needed
  • Supported data formats are JSON and RDF
  • Exporting database is explained here


  • Binary format
  • Both full and incremental backups to files, S3 and Google storage via Minio
  • Live backups with no downtime
  • Reference
  • Proprietary tarball per node
  • No live backup, must turn off writes for consistency.
  • Reference

Point in time recovery

On the roadmap No

Multi-region deployments



Management of runaway queries

  • Context cancellation which works across clients and servers. So, a context cancellation at the client level would automatically cancel the query at all involved servers
  • OpenCensus integration , which allows distributed tracing all the way from app to Dgraph cluster and back.
  • Open standards for query context cancellation and tracking
Yes via query timeout only

Pricing and Free trial

  • Open source version is under Apache 2.0, so free to use and modify.
  • Slash GraphQL (shared instances) starts at $9.99/backend/month.
  • Dgraph Cloud (dedicated instances) starts at $199/month. Bring-your-own-Kubernetes (BYOK) model is also available. Use the pricing calculator to estimate your monthly subscription.
  • Dgraph enterprise license is also available for self-hosted solution. Contact us for pricing.


  • Predicate-based sharding . Avoids N+1 problem and network broadcasts when running a query in high fanout scenarios. This ensures low-latency query execution, irrespective of the size of the cluster or the number of intermediate results. (Reference)
  • Consistent production level latencies and consistent queries (Reference )
  • Automatic sharding
Node-based sharding

High availability

  • Yes, HA Cluster Setup is explained here
  • HA Cluster setup is available in Community Edition.

Support for graph algorithms

  • Shortest k-paths
  • Edge traversal limit to determine cycles in graphs
  • Others requested from community listed here

Apache Spark integration

No Allows integration

Kafka integration

Yes Yes

Neo4j Migration tool

No No

SQL Migration tool

Yes No

Multi-database features

Yes Enterprise Edition Only MultiGraph

Graph Database As A Service (DBaaS)


Query execution plans

Yes No

Authentication and authorization

  • JSON web tokens (reference)
  • ACLs for enterprise license & Dgraph Cloud
  • Integration with LDAP on the roadmap

Transparent data encryption

Yes, database files are encrypted at rest with a user-specified key
  • No file-level encryption.
  • Encryption-at-rest relies on filesystem-level or disk-level encryption only (Reference).

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