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Month: February 2025

Comparing Oracle and PostgreSQL Transaction Systems

Published 2025-02-25 by Kevin Feasel

Laurenz Albe performs a comparison:

The transaction system is a core component of a relational database. It provides services that facilitate developing applications that guarantee data integrity. The SQL standard regulates some of the features of database transactions, but leaves many details unspecified. As a consequence, the transaction systems of relational databases can differ substantially. These days, many people are trying to get away from Oracle database and move to PostgreSQL. To migrate an application from Oracle to PostgreSQL, it is crucial to understand the differences between the respective transaction systems. Otherwise, you can end up with nasty surprises that may jeopardize performance and data integrity. So I thought it would be useful to compile a comparison of the features of transactions in Oracle and PostgreSQL.

Read on for that dive into how the two products compare.

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Aging Accounts Receivable Data in Power BI

Published 2025-02-25 by Kevin Feasel

Marco Russo and Alberto Ferrari inform us that we owe them money:

The Accounts Receivable (AR) Aging report helps companies track overdue receivables and better manage their cash flow. It is a common requirement from the finance department that often represents a challenge for Power BI reports, especially when you want to show the trend over time. Here is a typical visualization for the Open Amount at the end of each month, colored by the age range of the Accounts Receivable.

Read on for a dive into the report concept and some of the most common issues you may run into.

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Power BI Semantic Model Monthly Refresh via Fabric Data Pipelines

Published 2025-02-25 by Kevin Feasel

Chris Webb has another way for scheduling refreshes:

I’m sure you already know how to configure scheduled refresh for your semantic models in Power BI. While the options you have for controlling when refresh takes place are generally good enough – you can configure daily or weekly refreshes and set up to eight times a day for refreshes to take place – there are some scenarios it doesn’t work for, such as monthly refreshes. Up to now the workaround has been to use Power Automate to trigger refreshes (see here for an example) or to call the refresh API from another application. Now, with Fabric, you have a much better option for scheduling refreshes: Data Pipelines.

Click through for the demonstration.

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Defining “Laziness” in R

Published 2025-02-24 by Kevin Feasel

Maëlle Salmon, Athanasia Mo Mowinckel, and Hannah Frick are quite studious:

In the programming world, laziness can often be a good thing: it is both a human quality that can motivate automation efforts, and a programming concept that avoids wasting resources such as memory. Now, when reading code or documentation, seeing the word “lazy” can be confusing, because of its polisemy: it carries several meanings. In this post, we will enumerate the different possible definitions of “lazy” in R code.

Read on for a variety of contexts around “lazy,” including lazy evaluation, lazy database queries, lazy loading, and more.

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Building Sparklines in R Shiny

Published 2025-02-24 by Kevin Feasel

Osheen MacOscar needs a series of tiny visuals:

All of the plots from this package use the sparkline function, and we pass the type of chart we want as the type argument (default is line). The function will take a vector or list for the values argument, depending on the type of chart we are creating this can be either data to plot or specifications for the plot.

Click through for a list of the sparkline-esque visuals you can create as well as how you can use the sparkline package and some examples of outputs.

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Microsoft Fabric Permissions Models for Sharing Data with End Users

Published 2025-02-24 by Kevin Feasel

Jon Vöge builds a list:

Consider the following scenario:

  • I am building a data platform on Microsoft Fabric, using Lakehouses as the primary storage engine.
  • My end users need to consume data from the data platform as users of Power BI reports which connects to data from the Lakehouses, as developers of ad hoc models and report using data from the Lakehouses, and through ad hoc SQL queries on the Lakehouses.
  • I want to use DirectLake for Power BI reports to take advantage of frequency data ingestion and transformation, and improve the actionability of my reports.
  • My data is sensitive, and users, regardless of whether they consume reports or develop their own, need to be restricted by Row Level Security to only see some of the data.

Read on for eight different approaches to the problem and Jon’s thoughts on each approach.

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The Challenge of TDE in PostgreSQL

Published 2025-02-24 by Kevin Feasel

Bruce Momjian shares an update:

I first blogged about Transparent Data Encryption (tde) in 2019, which was more thoroughly analyzed in a blog post in 2023. An email exchange in December 2024 summarized the most up-to-date status of this feature:

When I started focusing on tde, it was going to require changes to buffer reads/writes, wal, and require a way to store secret keys. I thought those changes would be acceptable given tde’s security value. Once file I/O changes were required, I think the balance tilted to tde requiring too many code changes given its security value (not policy compliance value).

Read on for Bruce’s take now. Coming from the SQL Server world, where TDE has been in the product since 2008, I generally agree that there are better ways to ensure regulatory compliance. It’s not like TDE is actively harmful or anything, but considering that all of the relevant keys and certificates need to be on the local server to begin with, this prevents a limited number of situations from exposing your data, and there tend to be less resource-intensive alternatives for those situations.

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