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The Apache Hudi Asia meetup was full of energy with talks from Kuaishou, Huawei, ByteDance, JD.com, Meituan and more. Feels great to be part of such a vibrant; enterprising opensource community, that keeps “quietly”innovating the next big things for data

🎉The final brick in our open data lakehouse platform: OpenEngines. 🏄🌊 Over the past few years, we have been laying the foundation for something bold at Onehouse — a truly open-first architecture for the data lakehouse that can serve diverse data needs. Effectively, a cloud

Last week, we announced "OpenEngines" to flip the way data platforms are built, from being engine-centric to being data-centric. Other people have said that better. Check out this well-researched InfoWorld article. infoworld.com/article/396495… 🤺 "breaks the Siamese connection

🧠 Cloud Warehouses are now open ... Or are they? Open formats continue to be a hot topic, but how open is “open”? This blog series, “Towards Open Data,” aims to unpack the ground realities. 👉 Link to Part 1: onehouse.ai/blog/towards-o… Dipankar Mazumdar, M.Sc

New Blog: Cloud Data Warehouses now love Open Table Formats. But what does “open” really mean? Let’s unpack what's been really going on👇

💰 ⁉️What does running ETL on your cloud data platform cost you? 📈 💲 Short answer: very likely that it’s more than you think. Across all the performance-critical data systems I’ve worked on, the one thing that bugged me the most is: how poorly we benchmark Warehouse/Lakehouse

At #OpenXData virtual conference: Google BigQuery seems from implement the same approach of having an "internal" metadata format for managed #ApacheIceberg tables, the iceberg manifests etc are exported as read-only snapshots for access from other engines. This approach is

At #OpenXData "Bringing the Power of Google’s Infrastructure to your Apache Iceberg™ Lakehouse with BigQuery" talk Q: Are you able to comment on how the table types are distributed across BigQuery native format vs Iceberg/open table formats? A: Currently the vast majority of

#openai #codex We are some distance away from performing more complex tasks like rebasing a medium size PR touching 10s of files with >5 conflicts. But the experience is very exciting... AI is the future of software engineering, we will go through the usual phases : premature

🛬  We’ve upstreamed a good chunk of multi-catalog functionality from Onehouse to Apache XTable (Incubating) If you were wondering what the "X" meant, it meant "everything cross-table". XTable now operates beyond just the table format translation and helps across catalogs. 👉

Along with other exciting dbt news today, we’re thrilled to announce a powerful new integration between Onehouse and dbt Labs! 🔗 This is more than just a technical connection — it’s the unification of two universal paradigms: 1️⃣  Quanton by Onehouse brings cost-efficient ETL

This is some wise advice.

🧪 TPC-DI is better than TPC-DS for ETL workloads — but is it good enough? Read Databricks' recent take (and Shannon’s benchmark deep dive) with interest. It’s refreshing to see industry leaders debating real ETL performance, not just SQL query speeds. At Onehouse, we agree: ETL