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.
* No payment or form required
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.
Say goodbye to complex ETL and specialized storage
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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
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.
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
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Step 4
Query your data in Gremlin or Cypher
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.
* No payment or form required
Tailored insights for every industry
From AI to finance to pharma, see how PuppyGraph unleashes industry-specific powers.
See PuppyGraph in action and try it yourself
Dive into our demos and explore the power of graph analytics. With open-source datasets and queries, it’s your turn to dig up insights.
Meet our power pack - PuppyGraph’s Partners
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Get started with PuppyGraph
PuppyGraph empowers you to seamlessly query one or multiple data stores as a unified graph model.
Developer Edition
- Forever free
- Single noded
- Designed for proving your ideas
- Available via Docker install
Enterprise Edition
- 30-day free trial with full features
- Everything in developer edition & enterprise features
- Designed for production
- Available via AWS AMI & Docker install
* No payment required