PuppyGraph
Category: AI Infrastructure
PuppyGraph is a graph query engine that lets enterprises and AI agents query existing data lakes, warehouses and databases as a unified graph with no ETL or data movement. PuppyGraph was founded in 2023. The company is led by Weimo Liu. Based in San Francisco, United States. Team size: 11-50. Total funding raised: $15M. Latest round: Series A. Key investors include Particle Future, defy.vc.
- Founded
- 2023
- Headquarters
- San Francisco, United States
- Team size
- 11-50
- Total funding
- $15M
Value proposition
Query relational tables as a graph in place, at petabyte scale with subsecond latency and no separate graph database or data duplication, so AI agents can follow relationships across thousands of enterprise tables.
Products and solutions
PuppyGraph 1.0 graph query engine (generally available), AI-assisted schema builder, built-in AI agent and MCP support, Gremlin and Cypher query support, free Docker developer edition, role-based access control, row-level permissions and SSO
Unique value
Zero-ETL graph query engine that decouples query from storage. Supports up to 3,000 tables as one graph, and rejects undefined relationships so agents cannot make unsupported join assumptions.
Target customer
Enterprise data and AI teams, security teams, and developers building AI agents and knowledge graphs on lakehouse/warehouse platforms
Industries served
Cybersecurity, Fintech/crypto, Supply chain, Fraud & financial crime, Healthcare & life sciences, Knowledge graph / GraphRAG
Technology advantage
Distributed graph query engine running directly on Iceberg, Delta/Databricks, Snowflake, ClickHouse, PostgreSQL, Microsoft Fabric and other sources. Benchmark: 10-hop query across billions of edges in 2.26s on a four-machine cluster. Team has Google F1, TigerGraph and LinkedIn infrastructure experience.
How they differentiate
Competitors are graph databases that require loading data into proprietary graph storage via ETL. PuppyGraph is a query engine that queries the existing data stores in place with a single copy of data, reducing cost and complexity.
Main competitors
Neo4j, TigerGraph, Amazon Neptune
Key partnerships
Databricks (first graph analytics partner for Unity Catalog), Google Cloud (BigQuery & AlloyDB), Amazon S3 Tables, Prevalent AI (Security Data Fabric integration)
Notable customers
AMD, Palo Alto Networks, Datadog, Netskope, Coinbase, Trend Micro, Baker Hughes, Sola Security, Clarivate
Major milestones
Product launched March 2024, $5M seed led by defy.vc (Nov 2024), Databricks Unity Catalog partnership, PuppyGraph 1.0 GA and $10M Series A led by Particle Future (Nov 2026)
Growth metrics
ARR grew 7x over the past year (figure undisclosed); 70% month-over-month growth in free developer edition downloads (2024); product launched March 2024
Market positioning
Positions itself as the data engine for enterprise AI agents and the first graph query engine, a zero-ETL alternative to dedicated graph databases.
Geographic focus
United States / global enterprise
About Weimo Liu
Ex-Google F1 Query team Software Engineer/Research Scientist; ex-TigerGraph; Ph.D. in Computer Science, George Washington University.
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Official website: https://www.puppygraph.com