Session: Apache XTable, cross table interoperability with Delta, Iceberg, and Hudi

Ashvin Agrawal, Research Software Engineer @ Microsoft

Dipankar Mazumdar, Staff Data Engineer Advocate @ Onehouse

Apache XTable is a new open source project incubating in the Apache Software Foundation that unlocks omni-directional interoperability between the popular lakehouse projects Delta Lake, Apache Iceberg, and Apache Hudi. With a budding community over the past year, XTable has proven to be a bridge of unification for the data lakehouse industry.

In this session, we will highlight what is new in the project and the community. We will review the technical details of how the metadata translation works and showcase real-world examples of how users have adopted the project. Watch this session to see a live demo of how to use XTable with a variety of open source query engines including Spark, Presto, Trino, Flink, and more.

Want to learn more? Check out these resources from our co-chair Onehouse:

Where & when?

Open Source Data Summit 2024 was held on October 2nd, 2024.

What is the cost of access to the live virtual sessions?

OSDS is always free and open for all to attend.

What is Open Source Data Summit?

OSDS is a peer-to-peer gathering of data industry professionals, experts, and enthusiasts to explore the dynamic landscape of open source data tools and storage.

The central theme of OSDS revolves around the advantages of open source data products and their pivotal role in modern data ecosystems.

OSDS is the annual peer hub for knowledge exchange that fosters a deeper understanding of open source options and their role in shaping the data-driven future.

Who attends OSDS?

OSDS is attended by data engineers, data architects, developers, DevOps practitioners and managers, and data leadership.

Anyone who is looking for enriched perspectives on open source data tools and practical insights to navigate the evolving data landscape should attend this event.

On October 2nd, 2024 we convened for discussions about:
  • Benefits of open source data tools
  • Cost/performance trade-offs
  • Building data storage solutions
  • Challenges surrounding open source data tool integration
  • Solutions for the cost of storing, accessing, and managing data
  • Data streams and ingestion
  • Hub-and-spoke data integration models
  • Choosing the right engine for your workload
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