PuppyGraph has introduced native integration with Managed Iceberg Tables on the Databricks Data Intelligence Platform, enabling organizations to execute complex graph queries directly on Unity Catalog-governed Iceberg Tables—eliminating the need for data movement or ETL pipelines.
Databricks Managed Iceberg Tables, launching in Public Preview at this year’s Data + AI Summit, offers full support for the Apache Iceberg REST Catalog API. This allows external engines, such as Apache Spark, Apache Flink, and Apache Kafka, to interoperate seamlessly with tables governed by Unity Catalog. Managed Iceberg Tables provide automatic performance optimizations, which deliver cost-efficient storage and lightning-fast queries out of the box.
By combining PuppyGraph’s in-place graph engine with the openness and scale of Managed Iceberg Tables, teams can now:
- Query massive Iceberg datasets as a live graph, in real-time
- Use graph traversal to detect fraud, lateral movement, and network paths
- Perform Root Cause Analysis on telemetry data using service relationship graphs
- Eliminate the need for ETL into siloed graph databases
- Scale analytics across petabytes with minimal operational overhead
Coinbase and CipherOwl are joint customers of Databricks and PuppyGraph. At the Data + AI Summit, both will share how graph analytics has powered their products and enabled real-time insights directly on managed lakehouses.
“This changes how graph analytics fits into the modern data stack,” said Weimo Liu, CEO of PuppyGraph. “Databricks’ new Iceberg capabilities provide a truly open, scalable foundation. With PuppyGraph, teams can ask complex relationship-driven questions without ever leaving their lakehouse.”
To learn more about how PuppyGraph integrates with Apache Iceberg and the Databricks Managed Iceberg Tables, visit the website here.
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