Implement Pagination for Millions of Records

Break free from the linear performance degradation of OFFSET-based pagination in enterprise systems. When processing millions of records, standard LIMIT and OFFSET clauses force database engines to scan and discard massive data volumes, causing exponential latency spikes. This session provides a rigorous implementation strategy for keyset-based cursor navigation. By leveraging unique, deterministic identifiers and B-tree lookups, your queries jump directly to the target result set. Learn to architect composite indexes that cover both filter and sort criteria, implement row-value constructors for clean tuple comparisons, and resolve result drift caused by concurrent inserts or deletions. We detail technical methods for handling total record counts via metadata tables and Redis, managing distributed database shards, and optimizing frontend performance with virtualized lists and deferred joins. Master the design of stable, scalable data retrieval layers, bypass common ORM performance pitfalls, and ensure consistent sub-second API latency regardless of dataset size. ##DatabasePerformance ##SQLOptimization ##ERPDevelopment ##SystemArchitecture ##BackendEngineering ##CursorPagination ##DataEngineering