MongoDB.local NYC 2025: Definire il database ideale per l'era dell'AI

Summary

MongoDB announced several product releases and platform updates aimed at supporting artificial intelligence and agentic workflows at MongoDB.local NYC. The release of MongoDB 8.2 arrives alongside integrations with Voyage AI embedding and reranker models designed to enhance data retrieval precision. In addition, MongoDB launched Search and Vector Search in public preview for both Community Edition and Enterprise Server deployments, bringing vector capabilities to self-managed environments. To assist organizations transitioning away from rigid legacy database systems, MongoDB also introduced the Application Modernization Platform, which combines AI-driven tooling and specialized migration expertise. Early benchmarks from the modernization platform demonstrate legacy migrations running two to three times faster while accelerating code rewriting tasks by an order of magnitude.

Context

Legacy relational database systems struggle to scale and adapt to the architectural requirements of modern artificial intelligence workloads. Enterprises also face steep costs and operational risks when attempting to modernize critical legacy systems that lack the state, memory, and retrieval mechanisms required by agentic AI applications.

Approach / What changed

MongoDB introduced MongoDB 8.2 and integrated Voyage AI embedding and reranker models for AI application development. The company released Search and Vector Search in public preview across MongoDB Community Edition and Enterprise Server, and launched the MongoDB Application Modernization Platform (AMP), an end-to-end platform utilizing AI-assisted tooling, proven methodologies, and specialized talent to migrate legacy systems.

Takeaways

• Search and Vector Search are now available in public preview for both MongoDB Community Edition and MongoDB Enterprise Server.
• The MongoDB Application Modernization Platform enables organizations to migrate from legacy systems two to three times faster and accelerates code rewriting by an order of magnitude.
• MongoDB integrates Voyage AI embedding and reranker models to bridge private enterprise data with large language models for agentic AI applications.

Related reading

• MongoDB · Sep 18, 2025

  MongoDB.local NYC 2025: Defining the Ideal Database for the AI Era

  At MongoDB.local NYC, MongoDB introduced new database capabilities, AI integrations, and modernization tools designed for agentic and generative AI workloads. The release of MongoDB 8.2 arrives alongside public previews of Search and Vector Search for both MongoDB Community Edition and Enterprise Server. MongoDB also highlighted Voyage AI embedding models and rerankers to improve retrieval accuracy across raw data, metadata, and embeddings. To address the costs and constraints of legacy infrastructure, the new MongoDB Application Modernization Platform combines AI-assisted tooling and specialized expertise to migrate legacy systems. According to MongoDB, early migrations using this platform run two to three times faster, while code rewriting tasks accelerate by an order of magnitude.

  Dev Ittycheria, President and CEO, MongoDB

• MongoDB · Sep 18, 2025

  MongoDB.local NYC 2025: Definiendo la base de datos ideal para la era de la IA