How to modernize Apache Hive using Google Cloud’s Lakehouse runtime catalog

For over a decade, the Apache Hive Metastore (HMS) has served as the de facto metadata authority for big data analytics. Whether it was deployed on Hadoop clusters, self-managed Compute Engine VMs backed by MySQL or PostgreSQL, HMS provided the central schema registry that let Apache Spark, Presto, and Hive query raw .parquet and .orc files. However, as enterprise data architectures scale to petabytes and span multiple query engines (such as Google Cloud Managed Service for Apache Spark, BigQuery, and Trino), legacy Hive Metastores often become critical operational bottlenecks.