Difference between Teradata and traditional RDBMS systems

In the context of Teradata and traditional RDBMS systems, there are several key differences:

1. Distributed architecture: Teradata employs a shared-nothing architecture where data is distributed across multiple nodes, whereas traditional RDBMS systems typically use a shared-everything or shared-disk architecture.
2. Massively parallel processing (MPP): Teradata utilizes MPP for processing queries in parallel across multiple nodes, resulting in faster query performance compared to traditional RDBMS systems.
3. Scalability: Teradata is designed for massive scalability and can handle large volumes of data and concurrent users more effectively than traditional RDBMS systems.
4. Performance optimization: Teradata offers advanced optimization techniques such as indexing and partitioning to enhance query performance, which may be more limited in traditional RDBMS systems.
5. Workload management: Teradata provides robust workload management capabilities for prioritizing and managing different types of queries, workloads, and users, which may be less sophisticated in traditional RDBMS systems.

By understanding these differences, interview candidates can demonstrate their knowledge of the unique features and strengths of Teradata compared to traditional RDBMS systems.