Onehouse

It's no secret that?? Snowflake users love their data cloud. But did you know you could reduce your ingestion costs with a #datalakehouse for ETL/ELT, and still deliver up-to-the-minute data to your Snowflake users? And with industry-first multi-catalog sync from Onehouse, you'll end up with a single “source of truth” copy of your data, for all use cases and all downstream engines - Snowflake, Databricks, Flink, Spark, and more. Join our webinar to see how it's done!

Scaling operations & onboarding new businesses rapidly is a key challenge faced by organizations today. In this talk from Amazon Engineering, speakers will discuss how they've built a config-driven system named Nexus, that allows them to create and alter workflows, business logic for the underlying data lake built on top of Apache Hudi, using only configurations. Amazon Unit Economics org produces unit-level profitability metrics for a lot of Amazon WorldWide Stores. To scale operations effectively and onboard new businesses rapidly, Nexus empowers finance teams to define their own use cases through configurations, which in turn drives workflow creation, business logic execution, and data persistence within Amazon’s Hudi-based data lake across different stages of the data lifecycle. This talk will provide insights into the challenges encountered during Nexus’s development, unique discoveries made due to the scale of Hudi’s use, and future plans for expanding its capabilities.

The Truth About Open Table Formats with Vinoth Chandar, this week on Catalog & Cocktails: The Honest No-BS Data Podcast! The data world is buzzing about open table formats and lakehouses, but what's the real story? Vinoth Chandar, founder & CEO of Onehouse, creator of Apache Hudi, unpacks the challenges of data siloes and vendor lock-in, and explains how open table formats are the key to unlocking true data flexibility and collaboration.

Apache XTable in Production! ?? So amazing to see this come out for public preview. Customers can now use Azure OneLake shortcuts to simply point to an Apache Iceberg table written using Snowflake or another Iceberg writer, and OneLake does the magic of virtualizing that table as a Delta Lake table for broad compatibility across Microsoft Fabric engines. This "metadata virtualization" is powered by Apache XTable, which takes the source Iceberg tables and atomically generates the corresponding Delta Lake metadata. This shows the robust capabilities of XTable in production use cases such as these which will be used by tens of thousands of users at scale. "Interoperability" is key to a lakehouse architecture's openness providing flexible access to multiple compute and catalogs. Blog: https://lnkd.in/dr-h6KMn #dataengineering #lakehouse

It's no secret that?? Snowflake users love their data cloud. But did you know you could reduce your ingestion costs with a #datalakehouse for ETL/ELT, and still deliver up-to-the-minute data to your Snowflake users? And with industry-first multi-catalog sync from Onehouse, you'll end up with a single “source of truth” copy of your data, for all use cases and all downstream engines - Snowflake, Databricks, Flink, Spark, and more. Join our webinar to see how it's done!

It's no secret that?? Snowflake users love their data cloud. But did you know you could reduce your ingestion costs with a #datalakehouse for ETL/ELT, and still deliver up-to-the-minute data to your Snowflake users? And with industry-first multi-catalog sync from Onehouse, you'll end up with a single “source of truth” copy of your data, for all use cases and all downstream engines - Snowflake, Databricks, Flink, Spark, and more. Join our webinar to see how it's done!