What is the principle behind the Teradata architecture?

The principles of Teradata architecture mainly consist of the following aspects:

1. Distributed architecture: Teradata uses a distributed architecture to store data across multiple nodes, each with independent computing and storage capabilities. This allows Teradata to achieve high concurrency, high reliability in data processing and querying capabilities.
2. Symmetric Multiprocessing (SMP) architecture: Teradata employs an SMP architecture where each node has identical processing power and storage capacity. This allows queries to be executed in parallel across multiple nodes, enhancing overall query performance.
3. Horizontal partitioning: Teradata divides data horizontally into multiple partitions and stores each partition on different nodes. This allows each node to be responsible only for querying and processing the data it stores, improving query concurrency performance.
4. Data distribution optimization: Teradata evenly distributes data across various nodes through data distribution optimization, allowing queries to be executed in parallel across multiple nodes. Additionally, Teradata utilizes data statistics information to intelligently select the data distribution method in order to enhance query performance.
5. The Access Module Processor (AMP) is a core component of the Teradata architecture, with multiple AMPs on each node responsible for reading, processing, and querying data. AMPs communicate through messaging to coordinate and synchronize, enabling distributed query processing.

Overall, the principle of the Teradata architecture is to disperse data storage across multiple nodes using technologies such as distributed, symmetric multiprocessing, and data distribution optimization, improving query performance and scalability through parallel execution and data distribution optimization.