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Introducing Onehouse Compute Runtime to Accelerate Lakehouse Workloads Across All Engines

Blog post from Onehouse

Post Details
Company
Date Published
Author
Kyle Weller and Rajesh Mahindra
Word Count
2,314
Company Posts That Month
5
Language
English
Hacker News Points
-
Post removed?
No
Summary

Open table formats (OTFs) for data lakehouses have revolutionized data infrastructure by promoting independent and decoupled data storage, as supported by Apache Hudi, Apache Iceberg, and Delta Lake. The Onehouse Compute Runtime (OCR) is a significant advancement in this field, offering a high-performance data processing runtime that enhances core data lakehouse capabilities, ensuring superior cost-effectiveness and performance across multiple engines without vendor lock-in. OCR integrates seamlessly with Apache Spark and provides features such as Adaptive Workload Optimizer, Serverless Compute Manager, and High-Performance Lakehouse I/O, addressing challenges related to workload optimization, resource management, and storage access. This innovation allows organizations to perform efficient data processing tasks like ingestion, ETL, and table optimization while maintaining control over their data, ultimately making it easier to manage and analyze data across various cloud platforms and tools.

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