MongoDB and Google Cloud’s collaboration enables customers to cost-effectively build and scale generative AI applications on their data.

MongoDB announced on the 15th that it will further strengthen its cooperation with Google Cloud at 'Google Cloud Next '24'.

This expanded collaboration will enable developers to cost-effectively build, scale, and deploy generative AI applications using MongoDB Atlas Vector Search and Google Cloud’s Vertex AI, and provide additional support for data processing with BigQuery.

The two companies provide a development environment suitable for data-driven applications for smart factories in the distribution and manufacturing sectors. New support for Google Distributed Cloud (GDC) for MongoDB Enterprise Advanced has also been added for running workloads based on sensitive data.

This collaboration enables seamless decoupling and scalability of generative AI applications. MongoDB Atlas Search Nodes are now available on Google Cloud, providing dedicated infrastructure for generative AI and relevance-based search workloads using Atlas Vector Search and MongoDB Atlas Search.

Customers can isolate workloads with Atlas search nodes separate from their core operational database nodes, optimizing costs and reducing query times by up to 60%. Additionally, enterprises can scale knowledge discovery workloads with Atlas vector search for autonomous AI agents without having to resize the entire database.

Additionally, dedicated VertexAI extensions make it easy to leverage large-scale language models (LLMs) such as Anthropic, Google Cloud, Meta, and Mistral without the need for data transformation or managing data pipelines between Atlas and Google Cloud. Developers can augment LLMs with their organization’s real-time operational data, and can even automatically generate queries for data operations and database operations with data stored in Atlas via natural language chat in the VertexAI console.

BigQuery can improve your analytics workloads with automated pipelines on operational data. BigQuery is a serverless enterprise data warehouse that is scalable and cost-effective for analytics, business intelligence (BI), and machine learning workloads across clouds. New integrations between Spark’s stored procedures and BigQuery enable you to automate, optimize, and reuse data processing workflows between BigQuery and Atlas for analytics, BI, and end-user applications.

Real-time application data can help you optimize your manufacturing and supply chain operations. Atlas enables you to securely store, process, and manage a wide range of real-time application data with high performance and scalability. The new Atlas integration with Google Cloud Manufacturing Data Engine helps you automate processes and optimize operations with modern real-time applications.

Composable commerce capabilities are being added for applications that deliver modern shopping experiences. MongoDB has joined Google Cloud’s Industry Value Network (IVN) partner program to help retailers build applications that deliver customer experiences at scale.

It enables you to run sensitive workloads in a secure, controllable environment. MongoDB is one of the first software companies to offer a verified solution on Google Cloud Ready, a distributed cloud program for customers running sensitive workloads. For government agencies, public institutions, and businesses in regulated industries that handle sensitive data, MongoDB Enterprise Advanced, available at GDC, enables you to build, deploy, and scale applications in air-gapped environments that are not connected to the Google Cloud or the public Internet.

“MongoDB’s strong partnership with Google Cloud is a result of our close collaboration to meet the needs of enterprises across a broad range of industries,” said Alan Chhabra, SVP of Partners at MongoDB. “Recognition as Google Cloud Partner of the Year in the Marketplace category recognizes MongoDB’s commitment to providing customers with best-in-class solutions to build modern applications, while also adhering to rigorous security and data privacy standards. We look forward to continuing to grow this partnership as more customers choose MongoDB and Google Cloud to power new types of generative AI applications.”

“Customers are asking us to embed world-class generative AI technologies into the tools they use most, like MongoDB,” said Stephen Orban, Vice President of Migration, ISV, and Marketplace, Google Cloud. “We’ve already helped thousands of joint customers successfully build and deploy applications with MongoDB Atlas for Google Cloud, and we’re continuing our strategic partnership to provide customers with more choices to quickly and effectively build and power applications with generative AI, including access to leading models with automated data pipelines through Vertex AI and BigQuery.”