MongoDB, the developer database, has added a new group of organisations to its AI development and services effort, the MongoDB AIApplications Program (MAAP) ecosystem.
MAAP was launched this summer, with founding members Accenture, Anthropic, Anyscale, Arcee AI, AWS, Cohere, Credal, Fireworks AI, Google Cloud, gravity9, LangChain, LlamaIndex, Microsoft Azure, Nomic, PeerIslands, Pureinsights, and Together AI. It offers customers an array of resources to put AI applications into production: reference architectures and an end-to-end technology stack that includes integrations with leading technology providers, professional services, and a unified support system to help customers quickly build and deploy AI applications.
Capgemini, Confluent, IBM, QuantumBlack, AI by McKinsey, and Unstructured have now all joined MAAP, giving enterprises additional integration and solution options. The MAAP Center of Excellence Team, a cross-functional group of AI experts at MongoDB, has collaborated with partners and customers across industries to overcome an array of technical challenges, empowering organisations to build and deploy AI applications.
MongoDB is also now collaborating with Meta on the Llama large language model platform to support developers in their efforts to build more efficiently and to best serve customers. Customers are leveraging Llama and MongoDB to build “innovative and AI-enriched applications”, said the partners.
“At the beginning of 2024, many organisations saw the immense potential of generative AI, but were struggling to take advantage of this new, rapidly evolving technology. And 2025 is sure to bring more change, and further innovation,” said Greg Maxson, senior director of AI GTM and strategic partnerships at MongoDB. “The aim of MAAP, and collaborations with industry leaders like Meta, is to empower customers to use their data to build custom AI applications in a scalable, cost-effective way.”
“Business leaders are increasingly recognising generative AI’s value as an accelerator for driving innovation and revenue growth. But the real opportunity lies in moving from ambition to action at scale. We are pleased to continue working with MongoDB to help deliver tangible value to clients and drive competitive advantage by leveraging a trustworthy data foundation, thereby enabling gen AI at scale,” said Niraj Parihar, CEO of insights and data global business line and member of the group executive committee at Capgemini. “MAAP helps clients build gen AI strategy, identify key use cases, and bring solutions to life, and we look forward to being a key part of this for many organisations.”
“We are pleased to see how many enterprises are leveraging our open source AI models to build better solutions for their customers and solve the problems their teams are facing every day,” added Ragavan Srinivasan, VP of product at Meta. “Leveraging our family of Meta models and the end-to-end technology stack offered by the MongoDB AI Applications Program demonstrates the incredible power of open source to drive innovation and collaboration across the industry.”
In another useful integration, for both database admins and application managers, Datadog, the monitoring and security platform for cloud applications, has announced its Database Monitoring product now observes MongoDB databases. Database Monitoring now supports the five most popular database types: MongoDB, Postgres, MySQL, SQL Server and Oracle.
Traditional monitoring tools typically only allow organisations to monitor either their databases or their applications. This can lead to slow and costly troubleshooting that results in frustration from database and application teams, extended downtime and a degraded customer experience.
Datadog Database Monitoring enables application developers and database administrators to troubleshoot and optimise inefficient queries across database environments. With it, teams can easily understand database load, pinpoint long-running and blocking queries, drill into precise execution details and optimise query performance to help prevent incidents and spiralling database costs.
“Replication failures or misconfigurations can result in significant downtime and data inconsistencies for companies, which may impact their application performance and reliability. That’s why maintaining high availability across clusters with multiple nodes and replicas is critical,” said Omri Sass, director of product management at Datadog. “With support for the top five database types in the industry, Database Monitoring gives teams complete visibility into their databases, queries and clusters so that they can maintain performant databases and tie them to the health of their applications and success of their businesses.”
