Now Available: Migrate from RU to vCore for Azure Cosmos DB for MongoDB via Azure Portal
Table of Contents
- Introduction
- vCore Model vs RU Model
- Migration Process to vCore
- Online and Offline Migration Support
- Free Migration and Benefits
Introduction
The new feature allows migrating from RU-based Azure Cosmos DB for MongoDB to vCore-based Azure Cosmos DB at no cost via the Azure Portal. It offers a cost-effective, simple, and efficient solution for modernizing workloads with improved performance and scalability within the Azure environment.
vCore Model vs RU Model
Azure Cosmos DB offers two pricing models: Request Units (RU) and vCore. The vCore model follows a traditional vCore-based provisioning approach, providing higher MongoDB compatibility, optimized scale-up performance, wider query surface area, seamless execution of extensive workloads, and complete support for MongoDB indexing. The vCore model is ideal for applications requiring predictable billing and efficient query execution.
Migration Process to vCore
Teams can migrate to vCore-based Azure Cosmos DB for MongoDB, adjusting schemas, maintaining data consistency, and fine-tuning performance to ensure a smooth transition while minimizing disruptions. The new feature aligns with migration strategies to ensure efficiency, scalability, and seamless data integrity, supporting both online and offline migrations with minimal disruptions.
Online and Offline Migration Support
The migration to vCore-based Azure Cosmos DB for MongoDB can be done using either online or offline methods without any additional costs. The feature analyzes partition key distribution, directs queries to appropriate partitions, and eliminates costly fan-out requests, ensuring a seamless transition with improved performance, scalability, and cost efficiency.
Free Migration and Benefits
The new migration feature enables users to modernize workloads with higher performance, scalability, and cost efficiency within the Azure portal for free. It provides SLA-backed speed, availability, instant dynamic scalability, making it ideal for real-time NoSQL and MongoDB applications that require high performance and distributed computing over massive volumes of NoSQL and vector data.