MongoDB to Azure Cosmos DB Migration using API for MongoDB- 8 Weeks

Secure, end-to-end migration of MongoDB document data (databases and collections) to Azure Cosmos DB using the Azure Cosmos DB API for MongoDB. The solution ensures reliable data transfer while preserving document structure and schema compatibility, enabling faster migrations, reduced risk, and validated outcomes.

Key Benefits

• Seamlessly migrate MongoDB databases, individual collections, or entire workloads to Azure Cosmos DB while preserving document structure.
• Reduce migration risk with built-in prechecks for connectivity, credentials, compatibility, and dependency validation.
• Achieve faster migrations through parallel reads, intelligent batching, and bulk write optimization tuned for Cosmos DB throughput.
• Maintain operational confidence with migration progress tracking, detailed logs, and migration history reporting.
• Validate outcomes using automated pre- and post-migration checks.

Agenda Timeline: 8 Weeks

1. Migration Strategy & Readiness Assessment (1–2 Weeks)
   • Understand the current MongoDB environment.
   • Identify the migration scope: database-level or collection-level migration.
   • Assess data volume, document size distribution, index strategy, and workload patterns.
   • Define success criteria, downtime tolerance, and the migration approach.

2. Environment & Connectivity Validation (1 Week)
   • Deploy the migration environment in Azure using ARM templates.
   • Provision and validate the target Azure Cosmos DB account configured with the API for MongoDB.
   • Validate target connectivity (connection string, firewall or VNet rules if applicable, and TLS).
   • Perform automated network and credential diagnostics.

3. Migration Planning & Configuration (1 Week)
   • Select migration mode and scope.
   • Configure data type mapping and compatibility handling for BSON types.
   • Configure the indexing strategy on the target environment.
   • Configure batch size, parallelism, retry/backoff policies, and throttling aligned with Cosmos DB throughput limits.

4. Migration Execution & Monitoring (1–2 Weeks)
   • Execute migration in controlled phases.
   • Run parallelized data extraction and bulk ingestion into Cosmos DB with real-time progress tracking.
   • Monitor migration performance and overall execution time.
   • Capture migration history and operational logs.

5. Pre- and Post-Migration Validation & Optimization (1–2 Weeks)
   • Validate data integrity through document counts per collection, key field verification, and sampling-based document comparisons.
   • Validate index readiness and query compatibility.
   • Verify application-facing behavior, including read consistency settings, connection configuration, and driver compatibility with Cosmos DB API for MongoDB.
   • Provide a post-migration summary including migrated databases and collections, document counts, collection sizes, and performance metrics.

Deliverables

• Migrated MongoDB databases and collections using a multi-select migration capability.
• End-to-end migration strategy covering collection-level or database-level migration.
• Migration History and Performance Report.
• Pre- and post-migration functional validation results.

Prerequisites

• Access to the source MongoDB environment.
• Access to a target Azure Cosmos DB account configured with API for MongoDB.
• Network connectivity between the migration environment and both source and target systems.
• Azure subscription access to provision migration infrastructure and Cosmos DB resources.

Target Audience

• Database Administrators (DBAs)
• Cloud and Infrastructure Architects
• Application Owners
• IT Operations and Platform Teams
• Enterprise Migration and Modernization Teams

Why MAQ Software

• Proven expertise in migrating document workloads from MongoDB to Azure Cosmos DB.
• Microsoft Solutions Partner with deep Azure and Cosmos DB platform expertise.
• Advanced migration tooling enabling high-speed, parallel, and validated migrations with complete operational visibility.
• Enterprise-grade support model focused on reliability, security, and minimal downtime.
• Customer-focused approach with tailored migration strategies based on workload scale, partitioning needs, and application constraints.