Abstract

Migrating from on-premises relational databases to cloud based NoSQL database [1] represents a fundamental shift in data architecture [2]. This transition involves moving from ACID-compliant [4], structured data models to eventually consistent, flexible schema designs. Organizations typically pursue this migration to achieve better scalability, reduce operational overhead, and leverage cloud-native capabilities. The process requires careful planning as it involves not just data movement but also application refactoring [5][20]. Modern database migrations can benefit significantly from GenAI [3] capabilities that can analyze source database patterns, predict optimal NoSQL targets, and automate complex decision-making processes. GenAI transforms traditional manual migration planning into intelligent, data-driven recommendations that reduce risks and improve outcomes. AI-powered analysis can examine years of query logs, schema evolution patterns, and performance metrics to recommend the most suitable NoSQL database type and architecture design. 

Keywords

  • Relational database migration
  • Cloud-based NoSQL
  • ACID compliance
  • Flexible schema
  • Data architecture transformation
  • Scalability
  • Operational overhead reduction
  • Cloud-native capabilities
  • Automated database migration
  • GenAI (Generative AI)
  • Schema analysis
  • Query pattern analysis
  • Data-driven decision-making
  • NoSQL database selection
  • Migration planning automation
  • Performance optimization
  • Risk mitigation
  • Intelligent migration tools

References

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