ReleaseBytes
gcp Google Cloud Blog ·

Google Cloud expands Data Cloud with real-time analytics, AI, and open tables

blogaiazuregcpgapreviewengineermediaenergygcp-bigquerygcp-cloud-sqlgcp-dataflowgcp-spannergcp-firestoregcp-lookergcp-composer
feature announcement

Google Cloud has rolled out a series of updates to its Data Cloud, focusing on real-time processing, enhanced AI integration, and open data formats. Key introductions include stateful continuous queries in BigQuery and new Apache Iceberg managed tables for Lakehouse, both in preview. Generally available features cover faster Dataflow pipeline updates, a synthetic data generator for Managed Kafka, and Airflow 3.1 with AI-powered troubleshooting. These advancements aim to provide engineers and architects with more flexible tools for building scalable, intelligent data solutions and leveraging AI agents.

  • →BigQuery adds stateful processing to continuous queries
  • →Managed Kafka gains synthetic data generator for quick testing
  • →Lakehouse managed tables for Apache Iceberg now in preview
  • →Managed Apache Airflow 3.1 with AI-powered troubleshooting
  • →Google Cloud enhances AI integration across BigQuery, Looker, and databases
Features (5) ›
  • BigQuery adds stateful processing to continuous queries

    This preview feature expands BigQuery continuous queries to support stateful operations like JOINs, aggregations, and windowing functions. It enables calculating time-based metrics for real-time applications and AI agents.

  • Managed Kafka gains synthetic data generator for quick testing

    Now generally available, this tool allows users to generate mock data for Kafka clusters in three clicks. It streamlines testing and feature validation without requiring client application modifications.

  • Lakehouse managed tables for Apache Iceberg now in preview

    Google-managed Apache Iceberg tables in Lakehouse are now in preview. They eliminate duplicate data pipelines and complex synchronization, providing native, multi-engine interoperability and automated table management.

  • Managed Apache Airflow 3.1 with AI-powered troubleshooting

    Managed Service for Apache Airflow launched new features, including the general availability of Airflow 3.1. It also adds AI-powered agentic troubleshooting, a managed MCP Server, and declarative YAML-based orchestration pipelines.

  • Google Cloud enhances AI integration across BigQuery, Looker, and databases

    Enhancements include the Gemini assistant in BigQuery Studio as a context-aware analytics partner and Conversational Analytics for Looker Embedded. Managed and remote MCP support for databases like AlloyDB, Spanner, and Firestore also powers next-generation AI agents.

Enhancements (1) ›
  • Faster, more flexible Dataflow pipeline updates with stop-and-replace

    Dataflow now supports stop-and-replace pipeline updates in parallel, accelerating migrations and reducing disruption. Users can also set drain timeouts to prevent runaway costs from stuck processing.

Read the original announcement →

https://cloud.google.com/blog/products/data-analytics/whats-new-with-google-data-cloud/

Related releases