Traditional data is structured and stored in tables using RDBMS, whereas big data handles massive volumes of structured, semi-structured, and unstructured data from multiple sources.

Traditional systems rely on centralized architecture and batch processing, while big data systems use distributed architecture and support real-time or near real-time processing.

Scalability and cost are major limitations of traditional data systems, but big data platforms are highly scalable, cost-effective, and flexible using commodity hardware and open-source tools..