PuppyGraph

PuppyGraph is the 1st graph analytics engine that can query one or more existing relational data stores as a unified graph model. No ETL required.

[PuppyGraph @puppyquery]

The PuppyGraph team is in Miami and bringing the heat 🌴🔥

We’re at @starburstdata #AIDataNova2026 with adorable puppy goodies and a whole lot of purple. You can’t miss us.

Come for the swag, stay for the graph talk. We’re talking knowledge graphs, security graphs, fraud graphs, and how to give your agents a semantic layer that understands connected data.

Stop by our booth and say hi 🐶💜

[PuppyGraph @puppyquery]

@daleverett This is cute! 🐶🐶🐾🐾

[PuppyGraph @puppyquery]

@wileycwj @daleverett @daltonmeon @damienhe @evokoa_ai @supabase @neondatabase We feel so understood 🥹🥹 thank you!! 😊

[Scott Haines @newfront]

If you’re in the Bay Area tomorrow and looking for an excuse to hang out with the @ApacheIceberg community. Come join us at the Bay Area Apache Iceberg meetup (https://t.co/920tD5c1tk)

Engineers from @awscloud, @puppyquery , @databricks, @Snowflake, @Cisco, hyperparam, supermetal, @LakeSailHQ, and @ZetaGlobal will keep you up to date on the latest and greatest.

[PuppyGraph @puppyquery]

Cool project and great minds alike!

Zhenni, cofounder of PuppyGraph here! Just want to clarify that thinking Puppygraph is not built for agentic workloads is simply wrong 😅 We have been empowering many big enterprises like AMD, Datadog and AI startups like Sola Security for their agent workloads.

In fact, many of our users told us that we’re the ONLY graph engine solutions that can query thousands of tables with < 3s performance. Not only we support PostgreSQL, we also support 20+ connectors, so many users use us as a federated query engine across all their data sources with zero ETL.

[PuppyGraph @puppyquery]

@Dhotachin Please join our slack https://t.co/rkUE6xItyc or send an email to [email protected] We can help you to setup everything.

[PuppyGraph @puppyquery]

𝗪𝗲 𝗽𝘂𝗹𝗹𝗲𝗱 𝘁𝗵𝗲 𝗹𝗼𝗴𝘀. 𝗧𝗵𝗲 𝗜𝗰𝗲𝗯𝗲𝗿𝗴 𝗠𝗲𝗲𝘁𝘂𝗽: 𝗥𝗦𝗔 𝗘𝗱𝗶𝘁𝗶𝗼𝗻 𝗿𝗲𝗰𝗮𝗽 𝗶𝘀 𝗹𝗶𝘃𝗲 🎬🧊
During one of the busiest cybersecurity weeks of the year, we stepped away from the RSA crowds and into the AWS SF office for a technical evening on Apache Iceberg and scalable cyber infrastructure.

One thing was clear from the room: Iceberg is showing up in more real production use cases. For RSA Edition, the focus was massive threat data, modern data lakes, investigation workflows, and where Iceberg fits into the cyber data stack.

Huge shoutout to the speakers who made the night worth the walk from Moscone:
🧊 Leticia Webb (@ClickHouseDB)
🧊 Colin Gibbens & Paul Agbabian (@splunk)
🧊 Peyman Mani (@cogent_security)
🧊 Austin Groeneveld (@awscloud)
🧊 Yiheng An & Chao Lei (@PaloAltoNtwks )
🧊 Weimo Liu (@puppyquery )

And thank you to our amazing co-hosts and organizers for bringing the community together:
Amy Krishnamohan • Nathan Yee (@awscloud), Zoe Steinkamp (@ClickHouseDB), Zhenni Wu • Jaz Samantha Ku (@puppyquery) 🎉

Couldn’t join us in March? Watch the highlights below 👇

And if you want to keep the conversation going, we’re back in the Bay Area on May 21 with @awscloud and @databricks 😎

Grab your spot here: https://t.co/WLp08xTqv6

#ApacheIceberg #Cybersecurity #DataLakehouse #DataEngineering #SecurityAnalytics

[PuppyGraph @puppyquery]

This melts our hearts 🥰

[Lonnie Jordan @LonnieJordan843]

Thanks @puppyquery ! You have helped find relationships between data that I never dreamed of! Everyone needs to learn about Knowledge Graphs, ontology, semantic fields and collocations. I honestly believe that the end of apps is near. Build a knowledge graph and create an OpenAPI to access it. Knowledge is power. I can see how this knowledge will open new doors and opportunities. @KGConference

[PuppyGraph @puppyquery]

Changing your graph schema shouldn’t mean 𝗿𝗲𝗹𝗼𝗮𝗱𝗶𝗻𝗴 all your data.

But with the traditional graph pipeline, that’s often the tradeoff:
📦 Move data into a graph database
🧩 Define the schema up front
🔁 Reload when the model changes

That slows teams down before they even get to the fun part: querying relationships.

With PuppyGraph, the data stays in tables while the graph schema sits logically on top.

Physically, tables.
Logically, a graph. 😎

Check out the clip below to see how this makes graph adoption much easier. 👇

#GraphAnalytics #GraphDatabase #DataEngineering #DataArchitecture #ZeroETL

[PuppyGraph @puppyquery]

Come wrap up spring with the 𝗕𝗮𝘆 𝗔𝗿𝗲𝗮 𝗜𝗰𝗲𝗯𝗲𝗿𝗴 𝗰𝗿𝗲𝘄 🧊🌸

@puppyquery is proud to co-host the @ApacheIceberg Meetup with @awscloud and @databricks, and you’ll want to be in the room for this one 👀

📅 𝗠𝗮𝘆 𝟮𝟭 | ⏰ 𝟱:𝟬𝟬–𝟴:𝟬𝟬 𝗣𝗠 |📍 𝗖𝗔𝗡𝗢𝗣𝗬 𝗠𝗲𝗻𝗹𝗼 𝗣𝗮𝗿𝗸

We’re bringing Iceberg builders together for an evening of technical talks, real production stories, and lessons that usually only come from doing the hard parts yourself.
Expect sessions on:

🐾 Iceberg in production, not just in theory
🐾 Architecture choices, technical lessons, and edge cases
🐾 What builders are learning as Iceberg matures
Plus plenty of time to swap notes, chat with other builders, and geek out with the Iceberg community.

And we’re not letting you leave hungry: unagi don, spicy stir fry, and more (desserts included!) 🍱🌶️

If you’re building on Iceberg, curious about Iceberg, or just want to meet the folks deep in the lakehouse weeds, come hang out.

🎟️ 𝗥𝗲𝗴𝗶𝘀𝘁𝗲𝗿 𝗳𝗼𝗿 𝗳𝗿𝗲𝗲: https://t.co/mBHi2bRSuC

🎤 𝗪𝗮𝗻𝘁 𝘁𝗼 𝗽𝗿𝗲𝘀𝗲𝗻𝘁? Submit your CFP here: https://t.co/nX4CdAjHMx

Big thanks to the organizers: Scott Haines and Lisa N. Cao (@databricks), Amy Krishnamohan and Nathan Yee (@awscloud), and Zhenni Wu, Weimo Liu, and Jaz Samantha Ku (@puppyquery) 🙌🙌

[RisingWave @RisingWaveLabs]

Cybersecurity questions are rarely about a single event or a single asset.

They are about relationships.

Which identities can reach which systems?
How do permissions connect across resources?
Where does exposure exist?
And if one system is compromised, what else becomes at risk?

Cyber attacks unfold in moments.
So, answering these questions requires tracing paths across the latest state of your infrastructure in real time.
But most security stacks are not built for that.

We are hosting a webinar with PuppyGraph to show what an architecture that actually solves this looks like.

Our speakers:
Yingjun Wu, Founder and CEO at RisingWave
WeimoLiu, Co-Founder and CEO at PuppyGraph

If you are working on security data, observability, or anything that requires tracing relationships across infrastructure in real-time, this webinar is for you!

Register here: https://t.co/E7gGcgQPXW

[PuppyGraph @puppyquery]

AI is changing cybersecurity on both sides: 𝘩𝘰𝘸 𝘢𝘵𝘵𝘢𝘤𝘬𝘴 𝘩𝘢𝘱𝘱𝘦𝘯, 𝘢𝘯𝘥 𝘩𝘰𝘸 𝘵𝘦𝘢𝘮𝘴 𝘳𝘦𝘴𝘱𝘰𝘯𝘥.

As models become more capable, they’re powering more sophisticated attacks while also enabling stronger defenses. This puts more pressure on the data layer to keep security context fresh, connected, and ready for real-time detection.

That’s what Weimo Liu @wmliu (@puppyquery ) and Yingjun Wu @YingjunWu (@RisingWaveLabs) will explore in our live webinar on cybersecurity + graph analytics on streaming data.

📅 May 7 | ⏰ 9:00–10:00 AM

This session looks at how to keep up:
🐾 Real-time data processing with RisingWave
🐾 Subsecond graph queries on fresh data with PuppyGraph
🐾 Faster detection with multi-hop reasoning across live relationships
🐾 An agent-friendly setup with ontology-enforced graph querying

We’ll use a cybersecurity demo to show how streaming data and graph queries can work together for faster investigation.

👉 Save your spot: https://t.co/rNpzkFAPJW

#Cybersecurity #GraphAnalytics #StreamingData #AIInfrastructure #DataEngineering

[PuppyGraph @puppyquery]

PuppyGraph is honored to be featured in the Google Cloud Lakehouse partner ecosystem.

For our team, this was a real moment to pause. Our logo is now sitting next to companies we’ve looked up to for years, in a space we’ve cared deeply about from day one.

Having PuppyGraph included in 𝘛𝘩𝘦 𝘨𝘰𝘷𝘦𝘳𝘯𝘦𝘥 𝘰𝘱𝘦𝘯 𝘭𝘢𝘬𝘦𝘩𝘰𝘶𝘴𝘦: 𝘈𝘤𝘩𝘪𝘦𝘷𝘦 𝘪𝘯𝘵𝘦𝘳𝘰𝘱𝘦𝘳𝘢𝘣𝘪𝘭𝘪𝘵𝘺 𝘢𝘯𝘥 𝘶𝘯𝘪𝘧𝘪𝘦𝘥 𝘤𝘰𝘯𝘵𝘦𝘹𝘵 with Ahmet Altay, Vinod Ramachandran, and Sumeet Singh made the moment feel even bigger.

We started with a simple belief: teams should be able to query their existing data as a graph, without moving it into a separate graph database. Seeing that idea become part of a broader lakehouse ecosystem means a lot.

As AI agents create new demands for context, semantics, and interoperability, we’re proud to help bring graph-powered context to lakehouse data.

No data movement. No new source of truth. Just connected context where teams already work.

Big thanks again to Jobin George, Talat Uyarer, and the entire Google Cloud team for the partnership and support that made this launch possible. 🙌

[PuppyGraph @puppyquery]

🎉 PuppyGraph is proud to be the launch partner for @Google Cloud Lakehouse! With support for the Iceberg REST Catalog API.

Unveiled today at #GoogleCloudNext 2026, GCP’s new Iceberg-native Lakehouse gives you open, managed #Iceberg tables. PuppyGraph turns those tables into an enforced ontology your AI agents can actually trust.

What does this integration gives you:
🐾 Multi-hop graph queries directly on Google Cloud Lakehouse data
🐾 An enforced ontology layer for AI agents
🐾 Sub-second performance at petabyte scale
🐾 openCypher + Gremlin on your existing tables (no graphDB required)
🐾 Built for agentic workloads, security, fraud, and more
When relationships matter, tables alone aren’t enough.
PuppyGraph adds structure on top of Lakehouse tables so agents can access context, validate queries, and recover when they get things wrong.

Big thanks to Jobin George, Talat Uyarer (@talatuyarer), and the entire Google Cloud team for the partnership and support that made this launch possible. 🙌

🎥 Teaser video below
📝 Full blog here: https://t.co/ZSQvjlWgtk

[PuppyGraph @puppyquery]

What a fun time at #DEOF2026 🐶

We had a blast meeting so many thoughtful data engineers and hearing how teams are architecting frontier solutions across AI, analytics, and modern data infrastructure. So many great conversations, big ideas, and inspiring builds packed into one event.

Safe to say the coffee cart was a hit… engineers need their caffeine ☕️

Huge shoutout to Xinran Waibel and @dataengthings for putting together such an awesome gathering. We’re so glad we got to be part of it.

#DEOF2026 #DataEngineering #GraphAnalytics #AIInfrastructure #DataArchitecture

[PuppyGraph @puppyquery]

@VeloDB_IO We really appreciate your teamwork!

[VeloDB (Powered by Apache Doris) @VeloDB_IO]

See how to query Apache Doris data as a graph:

@puppyquery lets you run graph queries directly on Apache Doris. No need for ETL into a dedicated graph database.

Use Cases:
- Cyber Security
- Anti-Fraud
- Fail Text-to-SQL
- Supply Chain

🔗https://t.co/Kfl2pDgec8

[PuppyGraph @puppyquery]

Knowledge graphs ≠ ontologies 😶‍🌫️

As LLMs and agentic systems start depending on structured, meaningful data to reason over, both terms keep coming up. Often in ways that blur together.

That is where things get messy.

The confusion doesn't just live in terminology. It shows up in how teams model data, scope graph projects, and think about semantics in production.

These concepts are related, but treating them as the same thing leads to the wrong architecture and the wrong expectations.

We'll explore what each one does, how they work together, and what that looks like in practice.

Full breakdown in the blog 📖 Link at the end of the carousel 👀

#KnowledgeGraphs #Ontology #LLMInfrastructure #AgenticAI #DataArchitecture