Hi Community,
TigerGraph is already in use in my Organization ( other team ) and I want to explore Dgraph.
So, I would like to know your opinions on why we should go with Dgraph.
Thanks
Shyam
Hi Community,
TigerGraph is already in use in my Organization ( other team ) and I want to explore Dgraph.
So, I would like to know your opinions on why we should go with Dgraph.
Thanks
Shyam
If you need a truly open-source graph database with no licensing constraints, Dgraph is preferable.
If your team is comfortable with GraphQL, JSON, or needs a simpler query language, Dgraph is more user-friendly.
For several real-world popular use-cases requiring vector storage and semantic search, like fraud detection, recommendation systems, or any AI-driven queries, Dgraph has a clear advantage with its native vector capabilities.
The advantages of relationship-based sharding over traditional entity-based sharding are pretty well known wrt performance so if you need an easy-to-scale, distributed graph database, Dgraph offers high-performance sharding and replication features.
If you want a lightweight, Kubernetes-friendly, and easy-to-deploy graph database, Dgraph is a better fit.
If you need fast streaming or batch ingestion, Dgraph provides a simpler and more scalable solution.
If you want GraphQL support for front-end or external applications, Dgraph is the superior choice.
Conclusion:
If you need a fully open-source, cloud-native, GraphQL-first, vector + graph hybrid, and highly scalable database, Dgraph is the better choice.
If you need advanced graph analytics with SQL-like querying** and are fine with proprietary licensing, TigerGraph may be suitable.
Thanks !!