This 4.99 MB dataset is well-suited for single-node deployment, with no immediate pressure to distribute infrastructure; at 16.6 KB per row across 300 records, it remains comfortably within typical in-memory processing budgets. The modest footprint suggests compression would yield minimal operational benefit—storage savings would be marginal relative to the computational overhead of decompression during analysis. The dataset is far below any meaningful scale threshold; it would need to grow 200–500× in size before distributed architecture becomes necessary for performance or cost reasons, making optimization efforts better directed toward query patterns and analytical efficiency rather than infrastructure redesign.