MongoDBOlivier ZielenieckiAnnouncement
우수성을 기념하기: 2025년 MongoDB 글로벌 파트너 어워드
Summary
MongoDB announced the recipients of its 2025 Global Partner Awards to recognize partner contributions across cloud modernization, artificial intelligence, and enterprise integration. Microsoft received the Global Cloud Partner award for Azure integrations, while Amazon Web Services secured the Global AI Cloud Partner award following joint generative AI implementations such as reducing workflow durations for Novo Nordisk. Google Cloud earned the Global Cloud GTM Partner distinction through shared sales development programs, and Accenture took Global SI Partner honors after establishing a dedicated engineering Center of Excellence. Confluent was named Global Tech Partner with more than 550 joint streaming deployments, and LangChain was recognized as Global AI Tech Partner for vector search and agentic frameworks. The awards demonstrate partner-led technical solutions spanning distributed databases, data streaming pipelines, and scalable enterprise cloud architectures.
Context
Organizations face challenges modernizing legacy systems, managing budget and security constraints, and deploying AI-driven applications across hybrid and multi-cloud environments.
Approach / What changed
MongoDB recognized its global ecosystem collaborators across cloud infrastructure, artificial intelligence, system integration, and data streaming through the 2025 Global Partner Awards.
Takeaways
AWS and MongoDB collaborated using Amazon Bedrock and MongoDB Atlas to reduce a Novo Nordisk workflow duration from 12 weeks to 10 minutes.
Confluent surpassed 550 joint customer deployments with MongoDB, focusing on event-driven streaming and multi-agent AI architectures.
LangChain and MongoDB expanded developer integrations for retrieval-augmented generation (RAG), hybrid search, and multi-agent memory workflows.
Source and freshness
- Source
- mongodb.com
- Published
- Added to Yomu
- Last updated
Summaries are generated from the original by a language model. Check the original before relying on it.
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