LLM-Assisted Database Migration Intelligence for Enterprise Platforms

Abstract

Enterprise database migration involves substantially more than copying schemas and records between systems. Organizations must translate incompatible data types, SQL dialects, stored procedures, triggers, indexing strategies, security models, and operational workflows while preserving application behavior and data integrity. Conventional migration tools automate common syntactic conversions but rely heavily on deterministic mapping rules, and they typically require substantial manual intervention once source systems contain proprietary features, dynamic SQL, undocumented dependencies, or business logic embedded in procedural code. This paper proposes an LLM-assisted database migration intelligence framework combining large language models, deterministic compatibility rules, retrieval-augmented generation, dependency analysis, and execution-based validation. The framework treats the language model as a reasoning and recommendation layer rather than an autonomous migration authority: it constructs a migration knowledge graph from schemas, database objects, application repositories, workload telemetry, and organizational standards, then classifies migration complexity, recommends target-compatible transformations, produces traceable remediation proposals, and validates generated artifacts through parsing, compilation, testing, data reconciliation, and performance comparison. An illustrative enterprise scenario shows how the architecture can support migration of a legacy transactional platform to a cloud-native relational database, and a proposed evaluation methodology outlines how transformation accuracy, semantic equivalence, migration coverage, engineering effort, and unsafe-generation rates could be measured in future empirical work. Large language models can materially improve migration discovery and engineering productivity, but only within a governed architecture that preserves deterministic validation, human approval, least-privilege access, and complete auditability.