Data warehouses

Conversational analytics in BigQuery is now available in the following locations:

northamerica-northeast1 (Montréal)

Amazon Redshift long-term system table retention with Amazon S3 Tables is now available in additional AWS Regions

Amazon Redshift long-term retention for system table data through native integration with Amazon S3 Tables is now available in additional AWS Regions.

You can export a conversational analytics agent's answer, including text, visualizations, tables, and citations, to a PDF or CSV file.

This feature is generally available (GA).

You can copy tables across regions.

This feature is now generally available (GA).

You can now use column aliases in GoogleSQL.

This feature lets you define an alias for an expression in the SELECT clause of a SQL query and immediately reference that alias within the same SELECT list or in the WHERE clause of the same query block.

The Apache Hive catalog endpoint in the Lakehouse runtime catalog is now generally available (GA).

This integration lets you use the metastore as a serverless, central metadata layer, enabling seamless data sharing and unified querying across Apache Spark, Apache Hive, and BigQuery.

The AI.AGG function now supports the output_schema argument, which lets you specify the schema of the function output as a comma-separated list of fields.

This feature is generally available (GA).

Metadata migration from Dataproc Metastore to Lakehouse is now generally available (GA).

You can perform a one-time backfill migration or dry run to migrate metadata from a Dataproc Metastore service to an Apache Iceberg REST catalog endpoint or a Hive catalog endpoint using the Google Cloud console, the gcloud CLI, or the REST API.

You can publish a BigQuery Conversational Analytics agent in Gemini Enterprise.

This feature is now generally available (GA).

Conversational analytics now lets you create a conversation with all of the data sources in multiple projects, or create a conversation with a dataset.

These features are generally available (GA).

The AI.AGG function is generally available (GA).

You can use this function to semantically aggregate unstructured input data based on natural language instructions.

BigQuery generative AI functions now support the gemini-4-argon model.

This model is generally available.

Incremental data transfers for the BigQuery Data Transfer Service for PostgreSQL and ServiceNow are now generally available (GA).

The BigQuery Data Engineering Agent is now available in the asia-northeast1 (Tokyo) regional endpoint and supports the gemini-3.5-flash model.

For more information, see Where Gemini in BigQuery processes your data.

BigQuery offers TimesFM 3.0, a built-in time series forecasting model that implements Google Research's open source TimesFM model.

You can use TimesFM 3.0 with the following functions:

Conversational analytics in BigQuery now supports the AI.CAUSAL_EFFECT function to quantify the impact of specific interventions on time series data.

This feature is in Preview.

Amazon Redshift adds support for creating and refreshing Apache Iceberg materialized views

Amazon Redshift now supports the creation and refresh of Apache Iceberg materialized views. Materialized views pre-compute expensive joins and aggregations once and store the results in an Apache Iceberg table in Amazon S3 or Amazon S3 table buckets, registered in the AWS Glue…

Announcing: Table discovery in OneLake Catalog search

Starting October 15, 2026, Search in Microsoft Fabric will return tables from semantic models, lakehouses, and mirrored databases as individual results. Users can search by table name or description, or find a table by an exact column-name match.

Iceberg external tables and Iceberg managed tables now support flexible column names by default.

This feature is generally available (GA).

The gemini-embedding-2 model works well for embedding long strings, including multilingual and unstructured data.

It supports a mix of text, images, audio, video, and PDF files. You can use this model in the AI.EMBED, AI.SIMILARITY, and AI.GENERATE_EMBEDDING functions. This model is generally available.