Teradata Data Loss Protection: Transient Journal, Fallback, RAID 1, and Clique
Learn how Teradata protects your data against potential loss with its various features. Each feature offers unique protection on different levels.
Architecture
Teradata Intelligent Memory: A Smart Strategy for Balancing Data Access and Storage Costs
Discover the benefits of Teradata Intelligent Memory and its unique approach to storing data. Learn how it prioritizes frequently accessed data for faster access.
Teradata Permanent Journaling: Snapshot Your Tables Before and After Changes
The Teradata Permanent Journal captures permanent table snapshots pre- and post-modifications. Prior to any changes, the original row duplicates are saved in the permanent journal table. This mirrors the behavior of the transient journal table, which stores BEFORE images of tables when a transaction begins. Journaling can be implemented at the table or database level. …
A Brief History of Parallel Database Architectures and Their Limitations
Discover the history of parallel database architectures – from shared memory to shared disk and shared-nothing. Learn about the advantages and limitations of each architecture and how fault tolerance is handled. Explore the shift towards big data and the trend of “Hadoop over SQL.”
Understanding Teradata Parsing Engine and Access Rights: Impact on System Performance
Learn about the Teradata parsing engine’s tasks and how it impacts overall system performance. Find out how to clean up the DBC. AccessRights table to improve parsing times in this informative article.
Column-Oriented Storage in Teradata: A Solution for Big Data Challenges
Learn about Teradata’s column-orientated storage, which offers an alternative way of laying out data on disks, benefiting data retrieval in Big Data times. This article explains how columnar tables work, how they differ from row-oriented databases, and how you can create them in Teradata 14.00.
Understanding the Relationship Between RDBMS and Hadoop: A Map Reduce Example
Discover how Map Reduce is becoming a key feature of most database vendors’ RDBMS. Follow an example of SQL aggregation statement joined with two tables.
Doing Teradata Hashing The Right Way
This article presupposes your existing familiarity with the fundamental structure of a Teradata System. As you are aware, the AMPs operate on a Teradata System. The number of AMPs responsible for managing rows stored on their respective virtual disks varies based on the system’s size. There may be hundreds of AMPs. As noted in my …
Maximizing Efficiency: Teradata vs. Snowflake Partitioning
Learn how Teradata and Snowflake minimize IOs to enhance performance. Teradata uses row partitioning while Snowflake relies on micro-partitions.
Understanding the Downsides of Data Lakes: Challenges and Pitfalls to Consider
Introduction Data lakes have gained significant popularity in recent years as organizations seek more flexible and scalable solutions to store and process their ever-growing volumes of data. While data lakes offer numerous advantages over traditional data storage and processing systems, they also have their fair share of challenges and pitfalls. In this critical article, we …