Teradata MERGE INTO vs. UPDATE This article compares the UPDATE statement to the MERGE INTO statement, analyzing their respective performance ...

Teradata MERGE INTO vs. UPDATE: Performance Comparison and Limitations

Introduction This blog post discusses tactical workloads on a Teradata system. Despite Teradata’s implementation of features that support tactical workloads, ...

Teradata Tactical Workload

1. Complete and up-to-date Statistics At the start of Teradata SQL Tuning, statistics are a vital concern. The Teradata Optimizer ...

The Importance of Up-to-Date Statistics for Teradata SQL Tuning

What is Teradata Query Rewriting? Teradata query rewriting is an integral component of the optimization process for Teradata. The optimizer ...

What is Teradata Query Rewriting? Top 6 Optimization Techniques Explained

It’s time to share a new Teradata SQL tuning case study that showcases the impressive impact of query rewriting on ...

Teradata SQL Tuning: How Query Rewriting Can Reduce Runtime from 40 Minutes to Seconds

1. Outline This showcase demonstrates optimizing statements with multiple JOINs using Teradata Optimizer’s tuning approach. The approach efficiently determines the ...

Optimizing Teradata Statements containing Multiple JOINS

Queries using the LIKE operator typically result in a full table scan. When the LIKE operator matches from the left, ...

Optimizing Queries with LIKE Operator in Teradata

When designing tables for Teradata, it is important to distribute the rows across all AMPs in the system evenly. For ...

Designing Small Reference Tables for Teradata: Storing All Rows on One AMP for More Efficient Queries

What is Partial Group By? Joins are costly. Before the introduction of PARTIAL GROUP BY, the join would be performed ...

Understanding Partial Group By: Reducing Join Costs with Aggregation Optimization

Improve the Performance of your Teradata System Executing the following query may reveal that a small number of queries are responsible for ...

Optimizing Teradata System Performance: Identify and Improve Resource-Consuming Queries