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.

Joined August 2023
136 Photos and videos
The PuppyGraph team is in Miami and bringing the heat ๐ŸŒด๐Ÿ”ฅ Weโ€™re at @starburstdata #AIDataNova2026 with adorable puppy goodies and a whole lot of purple. You canโ€™t miss us. Come for the swag, stay for the graph talk. Weโ€™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 ๐Ÿถ๐Ÿ’œ
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PuppyGraph retweeted
If youโ€™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 (luma.com/lvasrbqk) Engineers from @awscloud, @puppyquery , @databricks, @Snowflake, @Cisco, hyperparam, supermetal, @LakeSailHQ, and @ZetaGlobal will keep you up to date on the latest and greatest.
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๐—ช๐—ฒ ๐—ฝ๐˜‚๐—น๐—น๐—ฒ๐—ฑ ๐˜๐—ต๐—ฒ ๐—น๐—ผ๐—ด๐˜€. ๐—ง๐—ต๐—ฒ ๐—œ๐—ฐ๐—ฒ๐—ฏ๐—ฒ๐—ฟ๐—ด ๐— ๐—ฒ๐—ฒ๐˜๐˜‚๐—ฝ: ๐—ฅ๐—ฆ๐—” ๐—˜๐—ฑ๐—ถ๐˜๐—ถ๐—ผ๐—ป ๐—ฟ๐—ฒ๐—ฐ๐—ฎ๐—ฝ ๐—ถ๐˜€ ๐—น๐—ถ๐˜ƒ๐—ฒ ๐ŸŽฌ๐ŸงŠ 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: ๐ŸงŠ Leticia Webb (@ClickHouseDB) ๐ŸงŠ Colin Gibbens & Paul Agbabian (@splunk) ๐ŸงŠ Peyman Mani (@cogent_security) ๐ŸงŠ Austin Groeneveld (@awscloud) ๐ŸงŠ Yiheng An & Chao Lei (@PaloAltoNtwks ) ๐ŸงŠ Weimo Liu (@puppyquery ) And thank you to our amazing co-hosts and organizers for bringing the community together: Amy Krishnamohan โ€ข Nathan Yee (@awscloud), Zoe Steinkamp (@ClickHouseDB), Zhenni Wu โ€ข Jaz Samantha Ku (@puppyquery) ๐ŸŽ‰ Couldnโ€™t join us in March? Watch the highlights below ๐Ÿ‘‡ And if you want to keep the conversation going, weโ€™re back in the Bay Area on May 21 with @awscloud and @databricks ๐Ÿ˜Ž Grab your spot here: lnkd.in/gnjrHCka #ApacheIceberg #Cybersecurity #DataLakehouse #DataEngineering #SecurityAnalytics
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This melts our hearts ๐Ÿฅฐ
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
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Changing your graph schema shouldnโ€™t mean ๐—ฟ๐—ฒ๐—น๐—ผ๐—ฎ๐—ฑ๐—ถ๐—ป๐—ด all your data. But with the traditional graph pipeline, thatโ€™s often the tradeoff: ๐Ÿ“ฆ Move data into a graph database ๐Ÿงฉ Define the schema up front ๐Ÿ” 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. ๐Ÿ˜Ž Check out the clip below to see how this makes graph adoption much easier. ๐Ÿ‘‡ #GraphAnalytics #GraphDatabase #DataEngineering #DataArchitecture #ZeroETL
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Come wrap up spring with the ๐—•๐—ฎ๐˜† ๐—”๐—ฟ๐—ฒ๐—ฎ ๐—œ๐—ฐ๐—ฒ๐—ฏ๐—ฒ๐—ฟ๐—ด ๐—ฐ๐—ฟ๐—ฒ๐˜„ ๐ŸงŠ๐ŸŒธ @puppyquery is proud to co-host the @ApacheIceberg Meetup with @awscloud and @databricks, and youโ€™ll want to be in the room for this one ๐Ÿ‘€ ๐Ÿ“… ๐— ๐—ฎ๐˜† ๐Ÿฎ๐Ÿญ | โฐ ๐Ÿฑ:๐Ÿฌ๐Ÿฌโ€“๐Ÿด:๐Ÿฌ๐Ÿฌ ๐—ฃ๐—  |๐Ÿ“ ๐—–๐—”๐—ก๐—ข๐—ฃ๐—ฌ ๐— ๐—ฒ๐—ป๐—น๐—ผ ๐—ฃ๐—ฎ๐—ฟ๐—ธ Weโ€™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: ๐Ÿพ Iceberg in production, not just in theory ๐Ÿพ Architecture choices, technical lessons, and edge cases ๐Ÿพ 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 weโ€™re not letting you leave hungry: unagi don, spicy stir fry, and more (desserts included!) ๐Ÿฑ๐ŸŒถ๏ธ If youโ€™re building on Iceberg, curious about Iceberg, or just want to meet the folks deep in the lakehouse weeds, come hang out. ๐ŸŽŸ๏ธ ๐—ฅ๐—ฒ๐—ด๐—ถ๐˜€๐˜๐—ฒ๐—ฟ ๐—ณ๐—ผ๐—ฟ ๐—ณ๐—ฟ๐—ฒ๐—ฒ: luma.com/lvasrbqk?utm_sourceโ€ฆ ๐ŸŽค ๐—ช๐—ฎ๐—ป๐˜ ๐˜๐—ผ ๐—ฝ๐—ฟ๐—ฒ๐˜€๐—ฒ๐—ป๐˜? Submit your CFP here: forms.gle/pRNv8KRYscxnKrz5A?โ€ฆ 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) ๐Ÿ™Œ๐Ÿ™Œ
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PuppyGraph retweeted
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: luma.com/kv0l3y2t
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AI is changing cybersecurity on both sides: ๐˜ฉ๐˜ฐ๐˜ธ ๐˜ข๐˜ต๐˜ต๐˜ข๐˜ค๐˜ฌ๐˜ด ๐˜ฉ๐˜ข๐˜ฑ๐˜ฑ๐˜ฆ๐˜ฏ, ๐˜ข๐˜ฏ๐˜ฅ ๐˜ฉ๐˜ฐ๐˜ธ ๐˜ต๐˜ฆ๐˜ข๐˜ฎ๐˜ด ๐˜ณ๐˜ฆ๐˜ด๐˜ฑ๐˜ฐ๐˜ฏ๐˜ฅ. As models become more capable, theyโ€™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. Thatโ€™s what Weimo Liu @wmliu (@puppyquery ) and Yingjun Wu @YingjunWu (@RisingWaveLabs) will explore in our live webinar on cybersecurity graph analytics on streaming data. ๐Ÿ“… May 7 | โฐ 9:00โ€“10:00 AM This session looks at how to keep up: ๐Ÿพ Real-time data processing with RisingWave ๐Ÿพ Subsecond graph queries on fresh data with PuppyGraph ๐Ÿพ Faster detection with multi-hop reasoning across live relationships ๐Ÿพ An agent-friendly setup with ontology-enforced graph querying Weโ€™ll use a cybersecurity demo to show how streaming data and graph queries can work together for faster investigation. ๐Ÿ‘‰ Save your spot: luma.com/kv0l3y2t?utm_sourceโ€ฆ #Cybersecurity #GraphAnalytics #StreamingData #AIInfrastructure #DataEngineering
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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 weโ€™ve looked up to for years, in a space weโ€™ve cared deeply about from day one. Having PuppyGraph included in ๐˜›๐˜ฉ๐˜ฆ ๐˜จ๐˜ฐ๐˜ท๐˜ฆ๐˜ณ๐˜ฏ๐˜ฆ๐˜ฅ ๐˜ฐ๐˜ฑ๐˜ฆ๐˜ฏ ๐˜ญ๐˜ข๐˜ฌ๐˜ฆ๐˜ฉ๐˜ฐ๐˜ถ๐˜ด๐˜ฆ: ๐˜ˆ๐˜ค๐˜ฉ๐˜ช๐˜ฆ๐˜ท๐˜ฆ ๐˜ช๐˜ฏ๐˜ต๐˜ฆ๐˜ณ๐˜ฐ๐˜ฑ๐˜ฆ๐˜ณ๐˜ข๐˜ฃ๐˜ช๐˜ญ๐˜ช๐˜ต๐˜บ ๐˜ข๐˜ฏ๐˜ฅ ๐˜ถ๐˜ฏ๐˜ช๐˜ง๐˜ช๐˜ฆ๐˜ฅ ๐˜ค๐˜ฐ๐˜ฏ๐˜ต๐˜ฆ๐˜น๐˜ต 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, weโ€™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. ๐Ÿ™Œ
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๐ŸŽ‰ 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, GCPโ€™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: ๐Ÿพ Multi-hop graph queries directly on Google Cloud Lakehouse data ๐Ÿพ An enforced ontology layer for AI agents ๐Ÿพ Sub-second performance at petabyte scale ๐Ÿพ openCypher Gremlin on your existing tables (no graphDB required) ๐Ÿพ Built for agentic workloads, security, fraud, and more When relationships matter, tables alone arenโ€™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. ๐Ÿ™Œ ๐ŸŽฅ Teaser video below ๐Ÿ“ Full blog here: puppygraph.com/blog/puppygraโ€ฆ
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What a fun time at #DEOF2026 ๐Ÿถ 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 hitโ€ฆ engineers need their caffeine โ˜•๏ธ Huge shoutout to Xinran Waibel and @dataengthings for putting together such an awesome gathering. Weโ€™re so glad we got to be part of it. #DEOF2026 #DataEngineering #GraphAnalytics #AIInfrastructure #DataArchitecture
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PuppyGraph retweeted
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 ๐Ÿ”—velodb.io/blog/querying-apacโ€ฆ
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Knowledge graphs โ‰  ontologies ๐Ÿ˜ถโ€๐ŸŒซ๏ธ 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 ๐Ÿ“– Link at the end of the carousel ๐Ÿ‘€ #KnowledgeGraphs #Ontology #LLMInfrastructure #AgenticAI #DataArchitecture
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What inspired our zero-ETL architecture? We kept coming back to a pretty simple problem: Graph queries are great for complex, multi-hop questions ๐Ÿ“ˆ Moving all your data first? Not so much ๐Ÿ›‘ A lot of graph headaches start before you even get to the graph. So we asked: What would it look like to bring the Google approach to graph? #PuppyGraph #GraphQuery #DataArchitecture #ETL #GraphAnalytics
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PuppyGraph retweeted
Iโ€™m genuinely floored by this analysis. Itโ€™s rare to find someone who truly "gets" the ontology layer. Huge thanks to @drewcohenmoney. Our mission at @puppyquery is exactly this: Palantir-level power without an "army of engineers." Never felt so understood! ๐Ÿš€
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PuppyGraph retweeted
Thanks @puppyquery! 9131 nodes. 1,615,411 edges. 3364 persons, 2686 cases, 1361 documents, 468 true crime podcast shows, 712 locations. Visuals make Knowledge Graphs easy!
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