Teradata Architecture

 Simple explanation of Teradata Architecture

Teradata acts as a single data store, with multiple client applications making inquiries against it concurrently.
Instead of replicating a database for different purpose, with Teradata you store the data once and use it for all clients.
It provides the same connectivity for an entry-level system as it does for a massive enterprise data warehouse.
A Teradata system contains one or more nodes
A node is a term for a processing unit under the control of a single operating system.
The node is where the processing occurs for the Teradata Database there are 2 types of Teradata systems
Symmetric multiprocessing (SMP): An SMP Teradata system has a single node that contains multiple CPU’s sharing a memory pool.
 Massively parallel processing (MPP): Multiple SMP nodes working together comprise a larger, MPP implementation of Teradata.
The nodes are connected using BYNET, which allows multiple virtual processors on multiple nodes to communicate with each other.

3 main components

Parsing Engine
BYNET
Access Module Processor

Teradata and It’s unique features

The Teradata database is a massively parallel processing system running a “shared nothing” architecture.

The origin of the name Teradata is ‘tera’ derived from Greek which means ‘trillion’.

It is the first commercial database to support a trillion bytes of data.

Unique features

–> Parallel architecture

The Teradata Database provides exceptional performance using parallelism to achieve a single answer faster than a non-parallel system. Parallelism uses multiple processors working together to accomplish a task quickly. makes Teradata Database faster than other relational systems.

–> Single datastore

The Teradata Database acts as a single data store, instead of replicating database for different purposes with the teradata database we can store the data once and use it for all applications. The Teradata database provides same connectivity for all systems.

• can be accessed by network-attached and channel-attached systems.
• supports the requirements of many diverse clients.–> Scalability

Scalability is nothing but we can add components to the system, the performance increase as linear. Scalability enables the system to grow to support more users/data/queries/complexity of queries without experiencing performance degradation.

–> capacity

includes:
• Scaling from Gigabytes to Terabytes of detailed data stored in billions of rows.
• Scaling to thousands of millions of instructions per second (MIPS) to process data.

–> fault tolerance
automatically detects and recovers from hardware failures.
–> data integrity
ensures that transactions either complete or rollback to a stable state if a fault occurs.