Databricks launches on Google Cloud with integrations to Google BigQuery and AI Platform that unify data engineering, data science, machine learning, and analytics across both companies’ services. (press release)
Google Cloud and Databricks have announced a new partnership to deliver Databricks at global scale on Google Cloud. Under the partnership, organizations can now use Databricks to create a lakehouse capable of data engineering, data science, machine learning, and analytics on Google Cloud’s global, scalable, and elastic network. Databricks on Google Cloud will deeply integrate with Google BigQuery’s open platform and will leverage Google Kubernetes Engine (GKE), enabling customers to deploy Databricks in a fully containerized cloud environment for the first time. With this integrated solution, organizations can unlock AI-driven insights, enable intelligent decision-making, and ultimately accelerate their digital transformations through data-driven applications.
“Businesses with a strong foundation of data and analytics are well-positioned to grow and thrive in the next decade. We’re delighted to deliver Databricks’ lakehouse for AI and ML-driven analytics on Google Cloud. By combining Databricks’ capabilities in data engineering and analytics with Google Cloud’s global, secure network—and our expertise in analytics and delivering containerized applications—we can help companies transform their businesses through the power of data.”
said Thomas Kurian, CEO at Google Cloud
“This is a pivotal milestone that underscores our commitment to enable customer flexibility and choice with a seamless experience across cloud platforms. We are thrilled to partner with Google Cloud and deliver on our shared vision of a simplified, open, and unified data platform that supports all analytics and AI use-cases that will empower our customers to innovate even faster.”
said Ali Ghodsi, CEO and co-founder of Databricks.
“For Condé Nast, finding valuable insights from massive amounts of data is essential for creating world class content experiences that delight our global customers. Databricks on Google Cloud provides a lakehouse for our data engineers, data scientists and analysts to consolidate, collaborate, analyze, and use all of our global data to experiment and innovate quickly. We’re excited to see leaders like Google Cloud and Databricks come together to streamline and simplify getting value from data.”
said Nana Essuman, Director of Data Engineering at Condé Nast.
Deploying Databricks rapidly and securely at global scale
Global businesses need the ability to quickly deploy applications at any scale, and the elasticity to scale them up or down depending on their needs. Delivering Databricks on Google Cloud enables customers to rapidly provision Databricks on Google Cloud’s global network, with advanced security and data protection controls required for highly-regulated industries, and with the flexibility to quickly adjust usage based on the needs of the business.
Additionally, customers will soon be able to deploy Databricks from the Google Cloud Marketplace, enabling simplified procurement and user provisioning, Single Sign-On, and unified billing.
Advancing analytics with Databricks, BigQuery, and Google Cloud AI Platform
Databricks on Google Cloud is tightly integrated with Google BigQuery, giving customers the freedom of choice and access to their choice of data analytics services. With this integration, businesses can extend their existing Databricks lakehouse capabilities, now running on Google Cloud, and can cross-leverage Google BigQuery for analytics, ultimately simplifying their data investments, increasing usage, and creating new, data-driven business models and opportunities.
Unique integrations between Databricks and Google Cloud include:
Tight integration of Databricks with Google Cloud’s analytics solutions, giving customers the ability to easily extend AI-driven insights across data lakes, data warehouses, and multiple business intelligence tools.
Pre-built connectors to seamlessly and quickly integrate Databricks with BigQuery, Google Cloud Storage, Looker and Pub/Sub.
Fast and scalable model training with AI Platform using the data workflows created in Databricks, and simplified deployment of models built in Databricks using AI Platform Prediction.
Delivering containerized Databricks deployments for the first time
Databricks on Google Cloud represents the first container-based deployments of Databricks, on any cloud.
Increasingly, Kubernetes and containers are the de facto orchestration system for enterprise workloads and applications running in the cloud. Databricks on Google Cloud is built on GKE, Google Cloud’s secure, managed Kubernetes service, to support containerized deployments of Databricks in the cloud. By adopting GKE as an operating environment, Databricks is able to leverage managed services for security, network policy, and compute and as a result, provide customers with increasing business value through Databricks analytics, AI, and ML capabilities. Additionally, with GKE, Databricks increases its agility and the ability to accelerate the release of new features, quickly, at scale, and at lower cost.
Supporting open source innovation and partner collaboration
Databricks and Google Cloud share a commitment to open innovation and open source software. Under this new partnership, the two companies will continue to support the open source community, encourage open innovation and collaboration, making it easier for joint customers to build on open-source technologies.
Additionally, members of our joint ecosystem of partners have committed to ensure seamless integrations and expertise with Databricks on Google Cloud, including Accenture, Cognizant, Collibra, Confluent, Deloitte, Fishtown Analytics, Fivetran, Immuta, Informatica, Infoworks, Insight, MongoDB, Privacera, Qlik, SoftServe, Slalom, Tableau, TCS and Trifacta among others.
On April 6, join Databricks CEO, Ali Ghodsi, and Google Cloud CEO, Thomas Kurian as they share more about the partnership and vision of an open, unified data analytics platform during a discussion hosted by TechCrunch; visit the event page for more information.
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