Teradata is a popular Relational Database Management System (RDBMS) suitable for large data warehousing applications. It is capable of handling large volumes of data and is highly scalable. This tutorial provides a good understanding of Teradata Architecture, various SQL commands, Indexing concepts and Utilities to import/export data.

Audience

This tutorial is designed for software professionals who are willing to learn Teradata concepts and become a Teradata developer. By the end of this tutorial, you will have gained intermediate level of expertise in Teradata.

Prerequisites

You should have a basic understanding of Relational concepts and basic SQL. It will be good if you have worked with any other RDBMS product.

What is Teradata?

Teradata is one of the popular Relational Database Management System. It is mainly suitable for building large scale data warehousing applications. Teradata achieves this by the concept of parallelism. It is developed by the company called Teradata.

History of Teradata

Following is a quick summary of the history of Teradata, listing major milestones.

• 1979 − Teradata was incorporated.
• 1984 − Release of first database computer DBC/1012.
• 1986 − Fortune magazine names Teradata as ‘Product of the Year’.
• 1999 − Largest database in the world using Teradata with 130 Terabytes.
• 2002 − Teradata V2R5 released with Partition Primary Index and compression.
• 2006 − Launch of Teradata Master Data Management solution.
• 2008 − Teradata 13.0 released with Active Data Warehousing.
• 2011 − Acquires Teradata Aster and enters into Advanced Analytics Space.
• 2012 − Teradata 14.0 introduced.
• 2014 − Teradata 15.0 introduced.

Features of Teradata

Following are some of the features of Teradata −

• Unlimited Parallelism − Teradata database system is based on Massively Parallel Processing (MPP) Architecture. MPP architecture divides the workload evenly across the entire system. Teradata system splits the task among its processes and runs them in parallel to ensure that the task is completed quickly.
• Shared Nothing Architecture − Teradata’s architecture is called as Shared Nothing Architecture. Teradata Nodes, its Access Module Processors (AMPs) and the disks associated with AMPs work independently. They are not shared with others.
• Linear Scalability − Teradata systems are highly scalable. They can scale up to 2048 Nodes. For example, you can double the capacity of the system by doubling the number of AMPs.
• Connectivity − Teradata can connect to Channel-attached systems such as Mainframe or Network-attached systems.
• Mature Optimizer − Teradata optimizer is one of the matured optimizer in the market. It has been designed to be parallel since its beginning. It has been refined for each release.
• SQL − Teradata supports industry standard SQL to interact with the data stored in tables. In addition to this, it provides its own extension.
• Robust Utilities − Teradata provides robust utilities to import/export data from/to Teradata system such as FastLoad, MultiLoad, FastExport and TPT.
• Automatic Distribution − Teradata automatically distributes the data evenly to the disks without any manual intervention.