PuppyGraph is the first and only real time, zero-ETL graph query engine in the market, empowering data teams to query existing relational data stores as a unified graph model that deployed in under 10 minutes, bypassing traditional graph databases' cost, latency, and maintenance hurdles. Capable of scaling with petabytes of data and executing complex 10-hop queries in seconds, PuppyGraph supports use cases from enhancing LLMs with knowledge graphs to fraud detection, cybersecurity and more. Trusted by industry leaders, including Coinbase, AMD, Netskope, Palo Alto Network, eBay, and more.

How does PuppyGraph compare to Neo4j?

Unlike Neo4j, which requires you to load and sync data into its proprietary graph store, PuppyGraph runs directly on your data sources—eliminating ETL, reducing TCO, and enabling faster time-to-value. PuppyGraph also integrates natively with Databricks Unity Catalog, Google BigQuery, and AlloyDB.

What are the performance benefits of PuppyGraph?

PuppyGraph delivers multi-hop traversals in seconds over billions of edges. Real customer stories cite 5-hop queries on 1B+ edges in under 3 seconds.

Does PuppyGraph support my cloud data stack?

Yes. PuppyGraph natively integrates with Databricks Unity Catalog, Google BigQuery, AlloyDB, and AWS, keeping a single governed copy of your data.

How does PuppyGraph handle data governance and security?

PuppyGraph leverages your existing catalog and security (Unity Catalog, BigQuery, AlloyDB), so all graph queries respect your current access controls.

Can PuppyGraph power AI and LLM applications (GraphRAG)?

Yes. PuppyGraph enables Graph-based Retrieval Augmented Generation (GraphRAG) directly on your governed data—providing explainable, multi-hop context for LLMs and enterprise AI.

Query your relational data as a graph in real-time. Zero ETL.

PuppyGraph empowers you to seamlessly query one or multiple data stores as a unified graph model.

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deploy to query in

10 Mins

6-hop query across 600M edges in

< 1 Sec

in production for data volume of

5-10PB

📘 Hot off the press: The Apache Iceberg™ Digest Vol. 1: Catalogs, Graph, Maintenance, Streaming and Migration

Get the first-ever community Apache Iceberg™ digest from Confluent, Dremio, MinIO, Fivetran, and PuppyGraph. Inside you’ll find battle-tested insights on catalogs, streaming, graph, migration, and maintenance, written for It’s designed to help engineers and data teams deepen their Iceberg knowledge and learn from real-world experience across the ecosystem.

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Say goodbye to complex ETL and specialized storage

PuppyGraph is a very interesting graph query engine. It doesn’t require us to load or ETL any of the data into a specialized or proprietary database storage layer for graphs. PuppyGraph queries all our transactional and crypto data directly and performs all kinds of graph-based exploration and aggregation. It’s so powerful, and our users really enjoy this type of flexibility.

Eric Sun

Sr. Manager of Data Platform at Coinbase, at Data+AI Summit 2024

PuppyGraph’s relationship engine has been instrumental in building our correlation platform, enabling seamless connectivity and insights. The team’s efficiency, fast response, and proactive engagement have made a significant impact, providing us with valuable guidance every step of the way.

Naiming Chu

Vice President,
Infrastructure and Platform Operations, Netskope

PuppyGraph’s plug and play design is exceptionally user-friendly for newcomers to graph technology. We experienced virtually no learning curve, swiftly showcasing our first demo to the leadership team. Moreover, PuppyGraph did not increase our system complexity because it eliminated the need for data duplication, making the daily maintenance cost very low.

Po-Chun Chang

Engineering Manager, Protocol Labs

After evaluating a few different graph solutions, we struggled to find one that could scale to our data needs. PuppyGraph's approach, decopling the query engine from the storage, enabled us to connect to our data files and perform analytics across different data categories, this could assist with unlocking insights and new possibilities.
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Hongliang Liu

Director of Data Science at Clarivate

We found that GPEs like PuppyGraph—especially in cached mode—excel at analytical and summarization use cases, outperforming most graph databases by a wide margin.

Namith Cholappurath

Head of Architecture, PrevalentAI

Historically, graph queries required specialized storage and compute, but now PuppyGraph is running directly on plain vanilla Iceberg tables. Just point to a table with your nodes and edges, and let PuppyGraph go. The performance you get out the other side is amazing.

Jason Reid

Co-Creator of Apache Iceberg and Co-Founder of Tabular

In traditional architectures, working with graph data usually means ETL into a dedicated graph database like Neo4j, TigerGraph, or DataStax—which adds complexity and cost. Here, this is a different route: plug a graph engine directly into your Iceberg lakehouse. Simple, unified, and more cost-effective.

Bruno Marquié

Senior Principal Engineer, Sumo Logic

Natively integrating with all your favorite data sources

Deploy to query in 10 minutes

Step 1

Launch PuppyGraph in Docker

Step 2

Connect PuppyGraph to a relational data source

Step 3

Create graph schema

Step 4

Query your data in Gremlin or Cypher

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Single copy of data - query it in both SQL & Graph

Why choose between SQL and Graph? Prepare, aggregate, and manage data using SQL, and dive into graph queries for intricate traversals.

Why PuppyGraph

Zero ETL

Query your data as a graph directly from data warehouses and lakes, eliminating complex ETL pipelines and delays with PuppyGraph.

Petabyte-level scalability

PuppyGraph conquers scalability by auto-sharding across data sources, letting you graph-query petabytes of data directly from your warehouses and lakes without traditional constraints.

Complex queries in seconds

PuppyGraph can deliver a 10-hop neighbor query in 2.26 seconds across billions of edges with a 4-node cluster with our parallel processing and vectorized evaluation technology.

Deploy to query in 10 mins

As the first and only graph query engine, PuppyGraph eliminates onboarding hassles that comes with a graph database, letting you deploy and start querying within just 10 minutes.

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Tailored insights for every industry

From AI to finance to pharma, see how PuppyGraph unleashes industry-specific powers.