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Google Cloud's borderless Lakehouse unifies data across AWS, Databricks, Snowflake

By PulseAugur Editorial · [1 sources] ·

Google Cloud has introduced a new "borderless Lakehouse" initiative aimed at eliminating the need to copy data between different cloud platforms. The service, currently in preview, allows data pipelines and agents to directly access data residing in AWS Glue, Databricks Unity Catalog, and Snowflake Horizon through an Iceberg REST catalog. Additionally, Google is offering a flat-rate pricing tier for cross-cloud data transfers and has released an open-source Data Agent Kit that integrates with the Model Context Protocol, enabling AI agents to query federated data sources in natural language. AI

IMPACT Enables AI agents to access and process data across disparate cloud environments without costly data movement.

RANK_REASON This is a product announcement from a major cloud provider that integrates existing services and technologies, rather than a novel frontier model release or significant industry-wide shift.

Read on dev.to — MCP tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Google Cloud's borderless Lakehouse unifies data across AWS, Databricks, Snowflake

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This is a product announcement from a major cloud provider that integrates existing services and technologies, rather than a novel frontier model release or significant industry-wide shift.
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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High
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58 days old
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  1. dev.to — MCP tag TIER_1 English(EN) · Leo ·

    Google's borderless lakehouse wires AWS, Databricks and Snowflake catalogs into one Iceberg REST surface

    <p>The scene I keep replaying is from earlier this month. An agent in one of our data pipelines needed a metric that lived in Snowflake, a fact table that sat in an AWS bucket behind Glue, and one Delta table in Databricks that was the source of truth for a currency conversion. T…

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