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Data lake modernization

Google Cloud’s data lake powers any analysis on any type of data. This empowers your teams to securely and cost-effectively ingest, store, and analyze large volumes of diverse, full-fidelity data.

Benefits

Make the most of your data lake

Re-host your data lake

If you don’t want to rebuild your on-premises data lake in the cloud, lift and shift your data to Google Cloud to unlock cost savings and scale.

Burst a data lake workload

Take a resource-intensive data or analytic processing workload and burst it to the cloud to autoscale compute without provisioning new hardware.

Build a cloud-native data lake

Data lake turned into a swamp? A cloud-native data lake on Google Cloud can accelerate your data engineers’ and scientists’ analytics development.

Key features

Migrate Apache Spark and Hadoop based data lakes to Google Cloud

Fully managed services

Provision, autoscale, and govern purpose-built data and analytic open source software clusters such as Apache Spark for easier management in as little as 90 seconds.

Integrated data science and analytics

Build, train, and deploy analytics faster on a Google data lake with Apache Spark, BigQuery, AI Platform Notebooks, GPUs, and other analytics accelerators.

Cost management

Google Cloud’s auto-scaling services let you decouple storage from compute to increase query speeds and manage cost at a per-gigabyte level. Use custom machines, idle cluster deletion, and more to see up to 54% lower costs than an on-premises Hadoop deployment.

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