History of Teradata

Teradata is an open-source Database Management System for developing large-scale data warehousing applications. The tool supports several data warehouse operations at once using the concept of parallelism. Teradata is a massively open processing system that supports Unix/Linux/Windows server platforms.

Teradata software is created by Teradata Corporation, which is an American IT firm. It’s a supplier of analytics data platforms, applications and related services. The firm creates a product to combine data from various sources and make it available for analysis.

The history of Teradata

Teradata was an entity of NCR Corporation. It was incorporated in 1979 but split off from NCR in October of 2007. Michael Koehler became the first CEO of Teradata.

The Milestones for Teradata Corporation:

1979 – Teradata was incorporated into Teradata in 1979.
1984 – Release of first database computer DBC/1012
1986 1987 Fortune magazine named Teradata the “Product of the Year”
1999 – Largest database developed in the year 1999 using 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 that includes 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
20162015 Terada join hands with Big data
2017- Teradata Acquires San Diego’s StackIQ

Why Teradata?

Teradata offers a full suite of services that focuses on Data Warehousing
The system is built on open architecture. So whenever any faster devices are made available to the public, they can be incorporated into the already build architecture.
Teradata is able to handle more than 50 petabytes of data.
Single operation view for a large Teradata multi-node system using Service Workstation
Compatible with many BI tools that can fetch data.
It can act as an unifying point of reference in order for the DBA to manage the Database.
High-performance, diverse queries, in-database analytics and sophisticated load management
Teradata allows you to get the same data on multiple deployment options

In the next installment of this Teradata tutorial, we will learn about features of Teradata.

Features of Teradata SQL

Teradata provides these powerful features:

Linear Scalability: Offers linear scalability in dealing with massive amounts of data. This can be accomplished by adding nodes to improve the performance of the system.
Unlimited Parallelism: Teradata is based on MPP (Massively Parallel Processing Architecture). So, it is built to be parallel from the beginning. It is able to break down a huge project into smaller ones and run the tasks in parallel
Mature Optimizer: Teradata Optimizer is able to handle 64 joins the query.
Low TCO: Tera Data has an affordable total expense. It is simple to set up and maintain. It is also easy to administer.
Load & Unload utilities: Teradata offers load and unload utilities for moving data into or out of the Teradata System.
Connectivity: This system can connect to channel-attached systems such as a mainframe or network-attached systems.
SQL: Teradata supports SQL to communicate with data stored in tables. It supports its extension.
Robust Utilities: Teradata provides robust tools to import and export data from or into Teradata SQL assistant systems like FastExport, FastLoad, MultiLoad and TPT.
Automatic Distribution: Teradata can distribute the data to disks automatically without involvement from a human.

In the next part of this Teradata SQL tutorial, we will explore Teradata Architecture.

Teradata Architecture

Teradata architecture is a Massively Parallel Processing Architecture.

Three important elements of Teradata are:

Parsing Engine
BYNET
Access Module Processors (AMPs)

Teradata Storage Architecture

Parsing Engine:

The Parsing Engine analyzes the queries and creates it’s execution program. It manages user sessions. It optimizes & sends an invitation to users.

In other words, when a user runs queries to insert entries, 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 has networking capabilities. It also retrieves the data and transmits the row to the AMP target.

AMP:

AMP is an acronym in the form of Access Module Processor. It is a database that stores data on disks. AMP perform the following tasks:

Manages a part of the database
Manages a portion of each table
Complete all the work required to generate a results set, including joining, sorting, aggregation, and join
Perform the management of space and locks

Teradata Retrieval Architecture

When a user runs queries to retrieve records and records, the Parsing engine will send an email to BYNET. Then, BYNET forwards the request for retrieval to appropriate AMPs.

AMPs search their disks in parallel and recognize the required records and forward the records to BYNET. BYNET forwards the information to Parsing Engine which will then be sent on to the user.

The next step in this Teradata Database tutorial, we will learn about Teradata SQL commands.

Types of Teradata SQL commands

Teradata Database supports following basic SQL commands:

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

The Teradata Database and Applications Teradata Database

Following are the top Teradata Applications:

Customer Data Management: Allows to maintain lasting relationships with customers.
Master Data Management: Helps to build a platform where master data is utilized for synchronization, storage, and storage.
Financial and Performance Management: Helps organization to enhance the speed and the quality of financial reporting. It helps reduce the cost of finance infrastructure, and proactively manage enterprise performance.
Supply Chain Management Enhance the supply chain processes that lead to improve customer service, shorter cycle times, and lower inventories.
Demand Chain Management: Helps to improve customer service and sales. It also assists companies to forecast what customers will want from their store item accurately.

Summary

Teradata meaning: Teradata is an open-source Database Management System for developing massive-scale data warehouse applications.
Teradata was an entity that was part of NCR Corporation. It was incorporated in 1979, but separated from NCR in October 2007
Teradata provides a wide range of services that concentrate on Data Warehousing
Teradata provides linear scalability when dealing with massive amounts of data. It does this by adding nodes that improve the performance of the system.
Three essential components of Teradata are 1) Parsing Engine 2.) MPP 3) Access Module Processors (AMPs)
Teradata offers a complete collection of products that fulfill the ETL and Data warehousing needs of any business
Teradata application is primarily used for Supply Chain Management, Master Data Management, Demand Chain Management, etc.