skip to Main Content


Last Updated:
Analyst Coverage:

Teradata was first incorporated in 1979, in the days when a “tera” byte of data was “big data”. It released the world’s first parallel data warehouse in 1984 and has been a (if not the) leader in the data warehousing space ever since. It became a public company in 1987 but was acquired by NCR four years later. Thereafter it regained independence from NCR in 1997 and, once again, became a public company in 2007. The company has made a number of significant acquisitions over the last decade, including Claraview, Aprimo, Aster Data Systems and others. In 2014 it acquired Think Big Analytics, which now forms the heart of Teradata’s consulting practices around big data, including AnalyticOps. In late 2017, it spun off Starburst as a company focused on the Presto SQL Engine.

teradata logo

Company Info

Headquarters: 17095 Via Del Campo, San Diego, CA 92127 USA
Telephone: +1 858 485 4000

Cover for Machine Learning and Artificial Intelligence

Machine Learning and Artificial Intelligence

How does ML/AI work, who are the vendors and why you should care?
TERADATA InBrief cover thumbnail

Teradata Vantage

Teradata Vantage effectively consists of a merger between what was previously simply Teradata Database, and Aster Analytics.
TERADATA InBrief cover thumbnail

Teradata Vantage 4D

Teradata Vantage is the only product that we are aware of that has all the 4D capabilities that you might need.
TERADATA InBrief cover thumbnail

Teradata AnalyticOps

Teradata AnalyticOps Accelerator is a software and services offering comprised of best practices, proven design patterns, and tried-and-tested code.
TIME SERIES MarketUpdate cover thumbnail

Time-Series and Temporal databases and analytics

Time-series databases represent the fastest growing database sector over the last two years.
00002554 - DATA WAREHOUSING MU cover thumbnail

Options for analytic databases and warehouses

This is a comparative analysis of products/vendors within the data warehouse and analytics platform space.
The cover of SQL Engines on Hadoop

SQL Engines on Hadoop

There are many SQL on Hadoop engines, but they are suited to different use cases: this report considers which engines are best for which sets of requirements.
00002526 - ANALYTIC OPS MarketReport cover thumbnail


AnalyticOps is about the reduction of friction around the delivery, operationalisation and ongoing monitoring and (change) management of analytic models.
Back To Top