The Teradata Database and the Intelligent Expansion of the Data Warehouse

In 2002 Teradata launched the Teradata Active Enterprise Data Warehouse, becoming a key player in the data warehouse and business intelligence scene, a role that Teradata has maintained until now. Teradata mixes rigorous business and technical discipline with well-thought-out innovation in order to enable organizations to expand their analytical platforms and evolve their data initiatives. In this report TEC Senior BI analyst Jorge Garcia looks at the Teradata Data Warehouse in detail, including functionality, distinguishing characteristics, and Teradata's role in the competitive data warehouse space.
As data grows “bigger,” gets increasingly complex, and runs faster, it still needs to be analyzed efficiently. Some companies have taken radical approaches to addressing the challenge of evolving their data analysis platforms specifically to match their existing data warehouse and new big data initiatives. With 30 years’ experience in the data warehousing space, Teradata takes an interesting approach, mixing rigorous business and technical discipline with well-thought-out innovation in order to enable organizations to expand their analytical platforms and evolve their data initiatives with products for supporting and combining the sometimes distant worlds of data warehousing and big data.

About Teradata

Teradata, a public company (Nasdaq: TCD) based in Dayton, Ohio, is the result of the work and vision developed in the late 60s and early 70s within the offices of Scientific Data Systems (SDS)—later part of Xerox Corporation—and the California Institute of Technology (CalTech).
In the late 1970s, with an initial investment of $25 and good use of their personal credit cards, Dr. Jack Shemer, Dr. Phil Neches, and other investors and founders, including David Hartke and Jerry Modes, formed Teradata in July 1979—now one of the most important database, data warehouse, and analytics providers in the marketplace.
Innovation on their side, just one year after the company’s founding, Teradata’s creators were able to raise $2.6 million (USD) in venture capital funding, and by 1981 were again able to raise $12 million (USD) in a second round of financing. 

Teradata’s road to the data warehouse space officially started in 1983 with the launch of its  first beta data warehouse appliance, the DBC/1012 Model 1, the foundation for Teradata’s  later dominance in the data warehousing arena. Some of the system’s innovations included  being specifically devoted to back-end database management for mainframes, and the  introduction of YNET, Teradata’s system for enabling parallel node interconnection (which  has evolved into BYNET, Teradata’s software-based high-speed and massive parallel  interconnect system).

Mike Koehler, Teradata’s CEO

Twenty years later, in 2002—after being acquired by NCR (formerly National Cash Register) in the 1980s and later by AT&T in 1991—and achieving success as one of the largest providers of database technologies in the world—Teradata launched the Teradata Active Enterprise Data Warehouse, becoming a key player in the data warehouse and business intelligence scene, a role that Teradata has maintained until now.

Along with its vast history and experience, Teradata has gained customers that span a vast number of industries and types of organizations. Well-known organizations such as Air Canada, Coca Cola, Ford Motor Company, and Electronic Arts are just a few of a large number of customers that currently use one or more of Teradata’s data management solutions. 

Teradata’s Database Engine

One of the most important aspects of Teradata’s approach for providing data warehouse and analytics solutions is that it does not provide a one-solution-fits-all type of system, but instead provides a number of different offerings for generic and specific data warehousing, data management, and data analytics.

Teradata’s experience in data warehousing has allowed the company to design and create a diverse set of solutions offered via hardware-software appliances or as software-based solutions.

The Teradata Database is the core engine for all of Teradata’s warehouse solutions, and it includes all the main features for handling information for analytical purposes. The Teradata Database offering is composed of:

The Teradata Database—the core for all Teradata’s data warehousing solutions, providing all the necessary elements for managing databases for data warehousing purposes and with capabilities for handling relational schemas, as well as:

  • Teradata Columnar, an addition to the core Database technology that was introduced in Teradata Database 14.0, which enables the database to handle both row- and column-based data organization
  • Teradata Temporal, allowing users to include a unique temporal database option for handling temporal data, enabling organizations to keep track of data changes over time, and giving special capabilities for storing, querying, and updating historical data.
Teradata Express—Teradata’s software offering for evaluation and development. One of the most interesting options of this offering is that it is available in three main delivery modes:
  • Teradata Express for VMWare, a full version of the Teradata Database configured for the VMWare appliance management platform
  • Teradata Express for Amazon EC2, the Teradata Database configured under the Amazon AWS Platform
  • Teradata Express for Windows, a version of the Teradata Database (version 12 or 13) for 32-bit Windows workstations and laptops

Of particular interest is that under its umbrella Teradata provides new, potential, and existing users with testing and development environments where they can evaluate the performance of the database for specific use cases, evaluate a new purchase, or put in place prototypes for later deployment within a Teradata production environment.

The Teradata Database: Power, Intelligence, and Adaptability

One of the main concerns, if not the biggest, when choosing a database in the context of data warehousing has to do with power and performance. Traditionally, this power and performance refers to the database engine’s ability to process large amounts of information for analysis purposes. But this is not all; especially in recent years, the information that companies need to handle and use keeps growing, changing, and getting more complex every day.

Those managing data warehouse infrastructures are dealing with increasing demands for shorter processing times, more space for data, and increasing complexity applied to analysis. Due to their transactional nature, relational databases are increasingly being put to the test and pushed to the limit to be able to deliver on these demanding requirements.

In this sense, Teradata has taken a holistic and expansive approach, incorporating new technologies in all of its products and offerings, especially within the Teradata Database, enabling users to make use of new technology in a transparent way. Users don’t necessarily need to know or care about storage or data interpretation and movement, and the Teradata Database takes the lead in performing intelligently without burdening the user with the details of data warehousing.

Core Features

Some of the general features of the Teradata Database include:

  • The ability to maintain up to 2,000 nodes, and a capacity that goes up to 234 PB. Support for both symmetric multiprocessing (SMP) and massively parallel processing (MPP)
  • A “cloud ready” architecture
  • A number of capabilities for enabling and delivering full query parallelism and balanced performance

The Teradata Database server is natively designed to be deployed under Linux but with client support for Windows, Mac OS, IBM z/OS MVS, and UNIX/Linux Platforms. Fully ANSI SQL compatible and native development can be done in PL/1, C, or COBOL, and Teradata allows native solution development.

To ensure connection, the Teradata Database relies on a wide number of connectors to disperse data sources, and additionally offers common open database connectivity (ODBC), Java Database Connectivity (JDBC), and object linking and embedding database (OLE-DB) drivers as well as a special series of plug-ins for third-party development tools (such as Eclipse and Java Message Service (JMS)).

Despite the fact that Teradata’s Database works mainly as part of its own data warehouse appliances, it has the ability to integrate with IBM’s or compatible mainframes and currently has an architecture that supports deployment in the cloud. 

Of course, it comes as no surprise that the database adds a wide number of tools and utilities for administration and heavy data management. Some are key to modernizing traditional data warehouse deployments and provide managing agility, such as Teradata’s load and export utilities (FastLoad, MultiLoad and Data Mover, and TPump, Teradata’s continuous load application). Also available are a complete set of portlets for workload management within the Teradata Active System package and a range of tools within the Teradata Analyst Pack for statistics and visual analysis.

Another of Teradata’s new modernizer tools is the Teradata Warehouse Miner, the R add-on for Teradata, and the Teradata Analytic Data Set (ADS) Generator, which gives the database the ability to incorporate advanced analytics natively within the context of the Teradata Database running on any of Teradata’s workload-specific platform family members.  

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