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Teradata Tutorial

Teradata is an open source Database Management System for developing large-scale applications for data warehousing. The tool supports simultaneous operations in multiple data warehouses by using the concept of parallelism. Teradata is an open processing system that can be used on Windows, Unix and Linux server platforms.

Teradata software is created by Teradata Corporation, which is an American IT company. It’s a provider of analytics data platforms, applications and related services. The company develops a product that consolidates data from different sources and make it accessible to be analyzed.

The history of Teradata

Teradata was an entity that was part of NCR Corporation. It was founded in 1979, but separated from NCR in the month of October. Michael Koehler became the first CEO of Teradata.

The Milestones for Teradata Corporation:

1979 – Teradata was integrated into the Teradata database in 1979.
1984 – First database computer, DBC/1012.
1986 1986 Fortune magazine named Teradata as “Product of the Year”
1999 – The largest database created with Teradata using 130 Terabytes of data
2002 – Teradata V2R5 version release , with Partition Primary and compression
2006 – The launch of Teradata Master Data Management solution
2008 . Teradata 13.0 was released along featuring Active Data Warehousing
2011 . – Purchases Teradata Aster and enters the Advanced Analytics Space
2012 – Teradata 14.0 introduced
2014 – Teradata 15.0 introduced
2015- Teradata Buys Apps Marketing Platform Appoxee
20162016 Terada join forces with Big data
2017- Teradata Acquires San Diego’s StackIQ

Why Teradata?

Teradata provides a complete suite of services that focus on Data Warehousing
The system is built upon an open architecture. Therefore, whenever faster devices become available they can be integrated into the existing architecture.
Teradata can handle 50+ petabytes worth of information.
Single operation view for a large Teradata multi-node system using Service Workstation
Compatible with a variety of tools for BI to retrieve information.
It could serve as an all-in-one point of control to allow the DBA to oversee the Database.
High-performance, diverse queries advanced analytics, in-database analysis and management of workloads
Teradata lets you access the same data across multiple deployment options

In the next part of the Teradata tutorial, we’ll discover the features of Teradata.

The features of Teradata SQL assistant

Teradata provides the following features that are powerful:

Linear Scalability: Provides linear scaling when dealing with massive amounts of data. It can be achieved by adding nodes to improve the efficiency of the system.
Unlimited Parallelism: Teradata was developed on the MPP (Massively Parallel Processing Architecture). It was specifically designed to be a parallel system from the beginning. It is able to break down a huge task into smaller ones and execute the tasks in parallel
Mature Optimizer: Teradata Optimizer is able to handle 64 joins within the query.
A low TCO Tera Data has an affordable total expense. It is simple to set up and maintain as well as to manage.
Load and Unload utilities: Teradata offers load and unload utilities that allow you to transfer data to and from the Teradata System.
Connectivity: The MPP system is able to connect to channel-attached systems such as a mainframe or network-attached systems.
SQL: Teradata supports SQL to communicate with tables that store data. It also provides an extension.
Solid Utilities: Teradata provides robust tools to import and export data from or into Teradata systems such as FastExport, FastLoad, MultiLoad, and TPT.
Automated Distribution Teradata is able to distribute data automatically to the disks without need for manual intervention.

The next step in the Teradata SQL tutorial, we will be learning about Teradata Architecture.

Teradata Architecture

Teradata architecture is an Massively Parallel Processing Architecture.

Three key elements that make up Teradata are:

Parsing Engine
Access Module Processors (AMPs)

Teradata Storage Architecture

Parsing Engine:

The Parsing Engine analyzes the queries and then prepares an execution strategy. It handles sessions for users. It optimizes and sends an email to users.

When a client runs queries to insert data, Parsing Engine sends the records to the message Passing layer. The Message Passing Layer, also known as BYNET is a hardware and software component. It provides networking capabilities. It also retrieves records and transmits the row to the AMP target.


AMP is an acronym in the form of Access Module Processor. It saves data on these disks. AMP perform the following tasks:

Controls a small portion of the database
Controls a specific portion of each table
Complete all tasks that are related to generating a results set, including joining, sorting, and aggregation
Manage space and lock

Teradata Retrieval Architecture

When a client executes queries to find records and records, the Parsing engine transmits an email to BYNET. Then, BYNET forwards the request for retrieval to the appropriate AMPs.

The AMPs scan their disks in parallel , and identify the necessary records, and then send the records to BYNET. BYNET transmits the data to Parsing Engine and then they will be sent directly to clients.

In the next part of the Teradata Database tutorial, we will be learning about Teradata SQL commands.

Different types of Teradata SQL commands

Teradata Database supports following basic SQL commands:

Data Definition Language (DDL) commands
Control Language (DCL) commands. Control Language (DCL) commands
Data Manipulation Language (DML) commands

Teradata Database Applications Teradata Database

The following are the most popular Teradata Applications:

Manages customer data: Aids to keep lasting relationships with customers.
Master Data Management: Aids to create an environment in which master information can be utilized to store, synchronize, and synchronize data.
Financial and Performance Management: Aids organizations to increase the speed and accuracy of financial reports. It helps reduce the cost of finance infrastructure and helps to proactively monitor enterprise performance.
Supply Chain Management: Enhance the supply chain processes that lead in providing better customer service, shorter time to cycle, and less inventories.
Demand Chain Management: Aids to improve customer service and sales. It also assists companies to forecast how much demand they will receive for their store product accurately.


Teradata means: Teradata is an open-source Database Management System for developing large-scale applications for data warehousing.
Teradata was an entity that was part of NCR Corporation. It was founded in 1979, but separated from NCR in October of 2007.
Teradata provides a complete suite of services that focus on Data Warehousing
Teradata provides linear scalability when dealing with huge amounts of data. It can be scalable by adding nodes to improve the efficiency of the system.
Three key components of Teradata are : 1) Parsing Engine 2.) MPP 3.) Access Module Processors (AMPs)
Teradata provides a full selection of products to satisfy the Data warehousing and ETL requirements of any company
Teradata application is mostly used to manage Supply Chain Management, Master Data Management, Demand Chain Management and more.