Google Cloud has announced the launch of BigQuery metastore, a new metadata service designed to help enterprises streamline metadata management across multiple query engines. The fully managed unified metadata service is compatible with Apache Iceberg and aims to reduce the complexities associated with metadata management.

The BigQuery metastore is built to provide processing engine interoperability while enabling governance, according to Google principal engineer Yuri Volobuev and senior product manager Vinod Ramachandran. This means that enterprises can now manage their metadata in a single, unified platform, regardless of the query engine they use.

One of the key benefits of BigQuery metastore is its ability to support multiple query engines, including BigQuery, Apache Spark, Apache Hive, Apache Flink, and the Iceberg table format. This is in contrast to traditional metastores and metadata management systems, which are often tightly coupled with specific data processing engines. By supporting multiple engines, BigQuery metastore eliminates the need for enterprises to maintain multiple copies of their data and metadata in respective metastores.

According to Google, this fragmentation can result in stale metadata, lack of visibility into data lineage, security, and access challenges, and a subpar user experience. By unifying metadata across engines, BigQuery metastore makes it easier for analytics engines to query one copy of the data with a single schema, whether the data is stored in BigQuery storage tables, BigQuery tables for Apache Iceberg, or BigLake external tables.

In addition to its unified metadata management capabilities, BigQuery metastore also provides a range of governance features, including automated cataloging and universal search, business metadata, data profiling, data quality, fine-grained access controls, data masking, sharing, data lineage, and audit logging. This enables enterprises to maintain a high level of data governance while still supporting self-service BI and ML tools to drive innovation.

BigQuery metastore is also a serverless service, which means that there is no setup or configuration required to scale workloads. This reduces the total cost of ownership for enterprises and provides a no-operations environment that is easy to manage.

This announcement comes on the heels of Google's introduction of Gemini, a generative AI-based chatbot, to BigQuery last year. Gemini was designed to aid with code generation, code completion, code explanation, and provide partitioning and clustering recommendations, among other features.

The launch of BigQuery metastore marks a significant milestone in Google Cloud's efforts to simplify data analytics and management for enterprises. By providing a unified metadata management platform that supports multiple query engines, Google Cloud is poised to help enterprises drive innovation and improve data governance.

As the data analytics landscape continues to evolve, the need for effective metadata management solutions will only continue to grow. With BigQuery metastore, Google Cloud is well-positioned to meet this need and provide enterprises with a powerful tool for managing their metadata.