Releasesby Ibis
Amazon S3 is now available on the Vercel Marketplace and v0 by Vercel
GA10 days agoUnverifiedAdded Oct 17, 2026
Amazon S3, including S3 Tables and S3 Vectors, is now available natively on the Vercel Marketplace and v0. Developers can provision and connect object, vector, and open table storage directly within Vercel.
Topics: Data integration, Vector search, Apache Iceberg, Developer tools
More Amazon S3 Tables and Vectors releases
Every Amazon S3 Tables and Vectors releaseAmazon S3 Tables now support up to 100 table buckets per AWS Region in an AWS account
Amazon S3 Tables now support up to 100 table buckets per AWS Region in an AWS account, increased from 10. This allows you to create up to 1 million tables per AWS Region in an AWS account.
Amazon S3 Tables now support all Apache Iceberg V3 data types
Amazon S3 Tables now supports all Apache Iceberg V3 data types and features, including deletion vectors and row lineage. Users can create new V3 tables or upgrade existing V2 tables to improve performance and storage efficiency.
Amazon S3 Vectors now supports metadata pre-filtering for higher recall on filtered searches
Amazon S3 Vectors now supports metadata pre-filtering, allowing users to evaluate filters before similarity searches. This improves recall for scoped queries by narrowing the search space based on attributes like tenant or category.
Amazon S3 Vectors introduces metadata pre-filtering for up to 5x higher recall on filtered search
Amazon S3 Vectors now supports pre-filtering, which evaluates metadata filters before running similarity search, returning up to 5x more of the matching vectors when your filter is selective. S3 Vectors also adds a prefix match operator ($startsWith) for filtering on values like paths and URLs.
Also shipped on Oct 14, 2026
AWS in October 2026Workspace-level package repositories for Databricks Apps are generally available
Workspace admins can now configure default Python and npm package repositories for Databricks Apps. Apps inherit the workspace configuration while still allowing app-level overrides. See Configure default package repositories .
The Apache Hive catalog endpoint in the Lakehouse runtime catalog is now generally available (GA)
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.
Metadata migration from Dataproc Metastore to Lakehouse is now 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.
Conversational analytics now lets you create a conversation with all of the data sources in multiple...
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You can publish a BigQuery Conversational Analytics agent in Gemini Enterprise
You can publish a BigQuery Conversational Analytics agent in Gemini Enterprise . This feature is now generally available (GA).
The AI.AGG function now supports the output_schema argument, which lets you specify the schema of the...
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).