An integrated, serverless Big Data platform for data-driven analytics using the same analytical engines invented and used by Google for nearly two decades.
Secure, global, high-performance, cost-effective and constantly improving. We’ve built our cloud for the long haul.
Tap into big data and Google's vast API library including Machine Learning to find answers faster and build better products.
Grow from prototype to production to planet-scale, without having to think about capacity, reliability or performance.
Today's applications are generating an unprecedented amount of data from diverse sources within your enterprise, extending out into the physical world where any device is capable of capturing important signals for analysis.
The volume of data being generated is increasing at dizzying rates. Highly unstructured, raw data can tell a story of your operations environment and your customers in a way that we can now tap efficiently at scale.
Analytics and machine intelligence at web-scale have been in Google’s founding DNA since the very early days. Google Cloud Platform surfaces the same analytical engines invented and used by Google for nearly two decades to help unearth insight in your business and operational environment.
Google Cloud Platform leads the industry in the ability to let you analyze data at the scale of the entire web, with the familiarity of SQL and in a fully managed, serverless architecture where backend infrastructure is fully handled on your behalf.
Our big data analytics products are able to scale automatically while you focus only on the business insight you want to uncover.
BigQuery is Cloud Platform’s fully managed data warehouse that lets you economically query massive volumes of data at speeds one would expect from Google.
Pay as you go, taking advantage of our pricing benefits and the scalability and security of Google’s world-class infrastructure to power your business insights.
Cloud Dataflow is an innovative, fully managed service for developing and executing a wide range of data processing patterns including ETL, batch computation, and stream analytics.
Express your computation with no switching cost as you use a single tool and programming model for both batch and continuous stream processing flows.
Companies standardized on great open source tools including Spark, Hadoop/MapReduce, Hive, and Pig, will find a natural transition in Cloud Dataproc. Never worry about your data pipelines outgrowing clusters as Dataproc lets you create and resize clusters quickly at any time.
Per-second billing on the underlying Compute Engine resources ensures you pay only for the resources that you use, and you can spin down to zero when your analysis completes.
Specific business questions you might ask in the future are difficult to predict. Never discard events and valuable metadata in your business environment — store them economically to mine insight later.
Choose from a variety of globally available storage products for your data, from managed SQL to NoSQL options, including our category-defining archival product Nearline.
The long-term opportunity for companies lies in applying Google’s heritage of machine learning and analytics at web-scale to real-world data relevant to your business.
Cloud Platform enables modest-sized teams to aggregate and run machine learning workloads on massive data to do predictive analytics. To disseminate the use of machine learning, Google has recently opened-sourced its library for machine intelligence TensorFlow and launched Cloud Machine
Learning products, including several pre-trained models usable out-of-the-box such as Cloud Vision API, Cloud Speech API, and Google Cloud Translation API.
Google has led the industry with innovations in data processing technologies such as MapReduce, Bigtable, and Dremel.
Now, Google is making the latest generation of its data processing tools available to everyone, including industry leading programming tools and programming models.
"Spotify chose Google in part because its services for analyzing large amounts of data ... are more advanced than data services from other cloud providers."Nicholas Harteau VP Engineering, Spotify
"Our technology strategy boils down to how fast we can empower our engineers to focus on building high-quality, innovative productivity tools. By moving to Google Cloud Platform and using Datadog to improve application monitoring, we can quickly launch new services and features that will help us succeed in a changing market."Garrett Plasky Technical Operations Manager, Evernote
"With Philips Lighting and Philips Hue, we don’t just sell light bulbs—we sell a way for lighting to change your home and life. We chose Google Cloud Platform to power Philips Hue’s backend because it scales instantly, freeing engineers to work on product development rather than managing infrastructure."George Yianni Head of Technology, Home Systems, Philips Lighting
Transform your business with Google Cloud Platform