Fivetran Introduces Managed Data Lake Service for Google’s Cloud Storage

Fivetran, Inc. announced the launch of its Managed Data Lake Service for Google’s Cloud Storage.

Building on the launch of the company’s Managed Data Lake Service last year, this latest expansion enables enterprises to centralize structured and unstructured data from over 700 connectors into Google’s Cloud Storage in a query-ready open table format. By integrating directly with Cloud Storage, the service extends Fivetran’s data lake capabilities, providing a scalable, cost-optimized, and high-performance foundation for AI, analytics, and modern workloads.

“AI requires vast amounts of high-quality data, but getting that data into the right format at scale is a major challenge,” said George Fraser, CEO, Fivetran. “Our Managed Data Lake Service for Cloud Storage automates the entire process — moving, organizing, and optimizing data in open table formats — so businesses can focus on leveraging insights and driving innovation rather than managing infrastructure.”

By leveraging the company’s 700+ connector ecosystem, enterprises can centralize large volumes of data in Google’s Cloud Storage, creating a foundation for training custom large language models (LLMs) and developing context-aware GenAI applications. This enables businesses to move from AI experimentation to deploying scalable, enterprise-ready solutions.

Fivetran Managed Data Lake Service enables organizations to maximize value of Cloud Storage by:

• Lowering data ingest compute costs while accelerating data movement into Google Cloud with high-performance pipelines.
• Automatically converting data to open table formats, including Apache Iceberg and Delta Lake, for better interoperability.

• Natively integrating with Google Cloud’s BigQuery metastore, ensuring data in Cloud Storage is cataloged for improved governance and compliance while enabling  users of Google Cloud’s BigQuery data platform to query it with the same speed, simplicity, and experience as native BigQuery tables

“Enterprises are working with larger and more complex datasets than ever before, and they need a seamless way to centralize and prepare that data for AI and analytics,” said Yasmeen Ahmad, managing director, data analytics, Google Cloud. “Fivetran’s Managed Data Lake Service for Cloud Storage helps businesses get their data into open table formats efficiently, so they can take full advantage of Google’s Cloud’s leading AI and data analytics capabilities without the operational overhead.”

Fivetran is already onboarding Cloud Storage customers, and expects this integration to improve efficiency and reduce costs for organizations deploying AI and data-driven applications.

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Building on the company’s strategic partnership with Google Cloud — where over 100,000 unique connectors are already in use — our expanded support for Cloud Storage as a destination with the firm’s Managed Data Lake Service allows our nearly 4,000 joint customers to capitalize on the flexibility and scale of data lakes while ensuring enterprise-grade compliance and governance. Fivetran simplifies data management by maintaining query-ready, open table formats, ensuring integration with Google Cloud’s AI and analytics ecosystem.

“At Quantiphi, we’ve seen firsthand how Fivetran’s seamless data integration capabilities enable us to deliver faster, more reliable AI and analytics solutions for our clients. Our partnership with Fivetran allows us to leverage their industry-leading data movement technology, ensuring that we can quickly and efficiently centralize and transform complex datasets into actionable insights,” said Bhaskar Kalita, executive head, financial services, Quantiphi. “This collaboration gives our clients the confidence to innovate and scale their AI initiatives, knowing they have a solid, secure data foundation that supports their most critical business decisions.“

Fivetran’s fully managed change data capture (CDC), table maintenance, and BigQuery Metadata catalog native integration ensure data stored in Google’s Cloud Storage is always up-to-date, secure, and ready to support production-grade AI applications.