Fivetran, the global leader in automated data movement, announced the expansion of its Managed Data Lake Service to support Google Cloud Storage. Following the successful debut of the service last year, this new integration allows enterprises to effortlessly consolidate data from more than 700 sources into Google Cloud Storage in open table formats that are immediately ready for analysis.
By offering native integration with Cloud Storage, Fivetran extends its robust data lake capabilities, delivering a scalable, cost-effective, and high-performance foundation tailored for AI workloads, advanced analytics, and modern data architectures.
“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 of 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.”
With Fivetran’s expansive connector ecosystem, enterprises can streamline the ingestion of both structured and unstructured data into Google Cloud Storage. This provides a powerful platform for training custom large language models (LLMs) and deploying context-aware generative AI solutions at scale — accelerating the shift from experimentation to enterprise-wide AI adoption.
Key Benefits of Fivetran’s Managed Data Lake Service for Google Cloud Storage:
-
Reduced compute costs and faster data movement through high-performance ingestion pipelines.
-
Automatic conversion of ingested data into open table formats like Apache Iceberg and Delta Lake, enhancing compatibility across tools.
-
Native integration with BigQuery’s metastore, ensuring datasets are cataloged for streamlined governance and enabling BigQuery users to query stored data with the same ease and speed as native 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 of Data Analytics at Google’s 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.”
Also Read: AtScale Boosts Databricks Genie with Semantic Layer
Fivetran is currently onboarding customers to the enhanced Cloud Storage integration and anticipates measurable improvements in efficiency and cost-savings for organizations running AI-driven and data-intensive applications.
This launch deepens Fivetran’s strategic collaboration with Google Cloud, where over 100,000 unique connectors are already in use. With nearly 4,000 joint customers, Fivetran now enables even more organizations to unlock the scalability and flexibility of data lakes — without compromising on governance, compliance, or performance. By maintaining open, query-ready formats, Fivetran simplifies integration with Google Cloud’s AI and analytics stack, allowing teams to spend less time on infrastructure and more time delivering insights.
“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 of financial services for 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 solution includes change data capture (CDC), table maintenance, and native BigQuery metadata catalog integration — ensuring data within Google Cloud Storage remains up-to-date, secure, and optimized to support production-ready AI deployments.