Databricks Expands Lakehouse Capabilities and Formats for AI-driven Data Analytics
Originally Published 2 years ago — by The Register
Databricks is expanding its approach to data lakes by introducing Universal Format (UniForm), which allows data stored in Delta Lake to be read as if it were Apache Iceberg or Apache Hudi. This move aims to simplify the compatibility issues between Delta, Hudi, and Iceberg, and broaden Databricks' appeal in machine learning and data warehouse-type workloads. Meanwhile, Snowflake has announced updates to its Iceberg Tables, aiming to eliminate data silos and support unstructured data lake-style workloads. The battle between Databricks and Snowflake in the data lake world continues, with both companies striving to offer a unified platform for data management and analytics.