Oracle 26ai: QUALIFY Under the Hood #JoelKallmanDay

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Analytic functions have been among my favorite Oracle SQL features ever since their introduction in Oracle 8i. I’ve used them extensively over the years, and I still remember how much easier they made many SQL problems that previously required rather complicated solutions.

Tom Kyte once described analytic functions as “the coolest thing to happen to the SQL language since the introduction of the keyword SELECT.” I couldn’t agree more.

But there was one thing I kept missing: the ability to filter directly on the results of analytic functions. With the new QUALIFY clause in Oracle 26ai, this is finally possible. It’s a relatively small addition to Oracle SQL, but a long-awaited and very welcome one.

Let’s see how it works – and then take a look at something rather surprising under the hood.

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Oracle 26ai: An Even Closer Look at JOIN TO ONE

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Sometimes the most interesting findings start with a simple question. After publishing my recent post on Oracle 26ai JOIN TO ONE, Iudith Mentzel pointed out something in one of the query transformations that looked perfectly logical – but turned out not to describe what Oracle actually does.

A small test led me one level deeper, from DBMS_UTILITY.EXPAND_SQL_TEXT to the CBO trace, and revealed another interesting aspect of JOIN TO ONE: the way Oracle handles its implicit LEFT OUTER JOIN.

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Oracle 26ai: A Closer Look at JOIN TO ONE

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With Oracle AI Database 23.26.2, Oracle introduced the new JOIN TO ONE syntax. As it happened, just a few weeks later, I was teaching an Oracle 26ai course for data warehouse developers, and we actually managed to take a first look at this brand-new feature. We found it interesting and promising – but it also immediately raised some critical questions. Our conclusion was clear: this deserves a closer look. And that is exactly what this blog post is about.

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CALENDAR Functions in Oracle 26ai – Part 2

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Do I Still Need a Time Dimension?

In the previous post, we explored the new CALENDAR functions introduced in Oracle 26ai — their syntax, strengths, and some subtle caveats. Now it’s time to look at the architectural question: if date logic has become easier to express directly in SQL, does that reduce the need for a dedicated time dimension in analytical models?

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CALENDAR Functions in Oracle 26ai – Part 1

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First Impressions and Practical Observations

Oracle AI Database 26ai (23.26.1) introduces new CALENDAR SQL functions. Having written countless nested TRUNC/ADD_MONTHS/TO_CHAR/LAST_DAY expressions over the years, I expected to love them immediately. They do simplify many scenarios — yet they also introduce nuances that require careful understanding before using them everywhere.

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Fix Optimizer Estimate Issues from Implicit Conversions #JoelKallmanDay

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This is not just another post about why correct data types matter. Most of you know that using the wrong data type in WHERE or JOIN conditions can trigger implicit conversions, prevent an index access path, and cause performance problems. But what if you can’t change the SQL statements, and you don’t want to redesign your data model? This post is about possible solutions in case of a wrong cardinality estimation due to an implicit data type conversion.

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MERGE and DML RETURNING clause in Oracle 23ai

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For a long time, we all “knew” that MERGE did not support a RETURNING clause. You can ask ChatGPT, Gemini, or Google, and the answer would still be the same: Nope, no luck! LLMs respond with confidence, and Google’s top results show various workarounds for the problem. I swear I saw the lifting of this restriction in the New Features Guide back when the version was still called 23c :-). Since I’m currently preparing a conference talk where this is relevant, I naturally wanted to check whether my memory was just playing tricks on me — or if it’s actually true.

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ORA-30926 in Oracle 23ai: What’s Changed?

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One of the topics I’ve found very interesting as I started blogging was the sometimes strange behavior of the MERGE statement, the reasons for ORA-30926 and what it has to do with write consistency. My first blog post about it was almost exactly ten years ago. Time for a follow up! Especially because there are some changes in Oracle 23ai.

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When Compression Expands: The Hidden Pitfalls of HCC

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Hybrid Columnar Compression (HCC) in Oracle Exadata is a prime example of how physical infrastructure can significantly enhance the efficiency of data management and analysis—when used correctly. This is an area that also affects developers and data engineers: what it is, how it works, and what to expect. If HCC is used in your project, then everyone on the team should be aware of it, including the specifics of what, where, and how it is implemented. Otherwise, there may be a few surprises, as in the example I encountered recently: instead of achieving the expected storage savings and improved performance, there was a huge increase in space consumption, along with negative performance effects. Read on to find out what happened.

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NOT IN vs. NOT EXISTS: The Negation Battle #JoelKallmanDay

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A year ago I wrote about the pitfalls of NULL values in NOT IN subqueries. This time I wanted to keep promises I made back then, dig a little deeper and also look at NOT EXISTS as another type of subquery used to filter out records based on negative matches. Is there any semantic difference and which is faster? Unfortunately, there are many myths and misconceptions around the usage of (NOT) IN and (NOT) EXISTS subqueries.

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