Z-ordering and Liquid Clustering both aim to improve Databricks query performance through data skipping. But when your data is skewed, one of them quietly becomes useless. A visual explanation of why — and how the Hilbert curve changes everything.
If you have spent any amount of time working with Teradata, you know that the Primary Index is one of the most important design decisions you make. It determines how data is distributed across AMPs and whether your joins are fast or slow. Choosing the wrong Primary Index is one of the most common causes …
There was a time when a single team could build an entire data warehouse. Not a team of forty. Not a team of sixty distributed across three continents and coordinated by a project management office that had never seen an execution plan. A team of five. Perhaps six, if one counts the person from Controlling …
Somewhere around 2020, the data world quietly arrived at a conclusion that Teradata engineers could have told you in 1984: SQL on a massively parallel architecture is a pretty good way to process large volumes of data. The path to get there was anything but quiet. It involved billions in capital, an entire generation of …
Why data warehouse professionals have been doing “bronze, silver, gold” for over 20 years. If you have been working in data warehousing for any length of time, the first time you heard about the “medallion architecture” you probably had one reaction: We already do this. You were right. The medallion architecture, popularized by Databricks as …
For many years, Teradata was the undisputed leader in large-scale data warehousing. Banks, insurers, and telcos built their most critical systems on it. Today, the market is very different. Cloud-native databases such as Snowflake, BigQuery, and Databricks have set new standards in elasticity and simplicity. The question is: what role will Teradata play in this …
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