Yingjun Wu (Yingjun Wu // Vibe Mode 🤘) from RisingWave pulled back the curtain on what really makes streaming Postgres data into Apache Iceberg tricky. He talked TOAST, wild schema changes, late-arriving data, and tiny files, then showed how they got a real-time CDC pipeline working

Yuval Yogev (Yuval Yogev) from Ryft dug into the real challenges of streaming data into Apache Iceberg. He covered small files, compaction, late-arriving data, and how to keep high-throughput pipelines running smooth without wrecking performance. Thanks to everyone who came

Yuri Zarubin from Amazon Web Services gave a super helpful and info-packed talk on how S3 Tables make Apache Iceberg storage way easier to manage. No more chaos, just clean, scalable setup that actually works. Thanks to everyone who came out to the NYC Apache Iceberg Meetup!

Huge shoutout to our CEO Weimo Liu (Weimo Liu) for showing how Apache Iceberg and graph analytics work together to catch fraud that hides in plain sight. He walked through a real fintech use case that used Iceberg tables and graph patterns to surface fraud rings and risky

Shubham Satish Baldava (Shubham Baldava) from OLake by Datazip shared how to rethink ELT for Apache Iceberg with lightweight, high-speed pipelines built in Golang. No Spark, no Flink, just fast, efficient ingestion and smart optimizations. Thanks to everyone who came out to the NYC Apache

Matthew Topol (Matt Topol) from Columnar gave us a great look at how Golang and Apache Arrow make working with Iceberg fast, simple, and scalable. He showed how to handle schema evolution, batch reads, and efficient writes using the iceberg-go library. Thanks to everyone

Sean Sullivan from Grubhub gave us a solid rundown on S3—the cloud storage backbone behind so many data platforms. He covered the nuts and bolts, best practices, and what not to do when working with S3 in the wild. Thanks to everyone who came out to the NYC Apache Iceberg

Zoe Steinkamp from ClickHouse showed how you can run lightning-fast analytics on Apache Iceberg without the usual pipeline headaches. Real stories, real speed, and smart tips for getting sub-second queries straight from your data lake. Thanks to everyone who came out to the

Roy Hasson (roy hasson) from Microsoft closed out the night with a look at the next big shift in data platforms. He unpacked how open table formats like Apache Iceberg and object storage are reshaping the landscape, from OneLake to OTF-as-a-Service and what it all means for data

Big shoutout to Jordano Mark from Dremio for breaking down how clustering and Z-ordering can supercharge your Iceberg queries. Lakehouse tuning never looked so good. Thanks to everyone who came out to the NYC Apache Iceberg Meetup! #ApacheIceberg #Dremio #IcebergClustering

New tutorial from Brenna Buuck on how to build a #cloudnative graph analytics stack without migrating your data. Query structured data as graphs, uncover relationships & streamline your analytics. PuppyGraph projectnessie Apache Iceberg blog.min.io/from-tables-to…

With PuppyGraph and yFiles, you can turn raw data into real-time, #interactive #visualizations that really make an impact. Whether you're spotting #fraud, tracking #security threats, or just trying to understand complex #relationships. 👉 Check out: yfiles.com/resources/how-…

This week's #DevToolsDigest includes news and resources from streamfold, PuppyGraph, anchordotdev, and more. heavybit.com/devtoolsdigest…

Why Aren’t Graph Databases Mainstream Yet? You’d think they’d be everywhere by now... but they’re not. Let's break down some of the real reasons why adoption has been slow. No, it’s not just about cost. Stay tuned to learn how how PuppyGraph tackles these issues!

How Does PuppyGraph Handle Concurrent Graph Queries? Need to run multiple graph queries at once?PuppyGraph handles it with lazy loading and smart caching to keep performance high, even on large datasets. When fresh data is required, it smartly pulls from MongoDB only as needed.

What Is GraphRAG and How To Build It? You probably already have graphs hiding in your relational data. PuppyGraph lets you create a logical graph layer directly on top of that data. This enables GraphRAG: data-aware chatbots that understand relationships, not just keywords.