A Fine Slice Of SQL Server
Hristo Hristov outputs some JSON:
JSON is a complex data type used for representing objects with various properties. With JSON you follow the key-value pattern where the key is a string and the value can be of different data types. What are some common ways to work with JSON in SQL Server?
Most of this looks like functionality that has been in SQL Server for the better part of a decade.
Leave a CommentGilbert Quevauvilliers continues a series on load testing a Microsoft Fabric lakehouse:
In today’s blog post I am going to show you how to set up the Lakehouse and Fabric notebooks so that you can then configure it to be ready to be used with the JSON file we created in the previous blog post.
Click through for links to the notebooks, as well as how all of the pieces fit together.
Leave a CommentAndy Brownsword automates a workflow:
When building Azure Logic Apps we can use the Azure Data Factory connector to start a pipeline. However that action simply triggers a pipeline and doesn’t wait for it to finish. If your downstream logic depends on the output – for example to collect a file – this can cause issues.
In this post I’ll demonstrate how to control the Logic App flow to wait for the pipeline to complete before proceeding.
Read on to see how, as well as some additional ideas of how to improve the pattern.
Leave a CommentOsheen MacOscar forces me into alliteration:
So far, in the previous blog we covered creating our package with Poetry, managing our development environment and adding a function. In the current blog post we’ll be covering the next steps with package development including documentation, testing and how to publish to PyPI.
Read on for several tips on making Python code package-ready and then how to distribute it via PyPi.
Leave a CommentJon Vöge declares a hostile takeover:
Now, how you best maintain multiple copies/variants of the same Semantic Model is a whole other discussion but as a one-off, I was asked to merge the Measures of the two models.
Initially, the question actually stumped me as my usual tool of choice for external manipulation of semantic models Tabular Editor does not have a great native way to solve this.
Jon lists a variety of options and then gets the job done with ALM Toolkit.
Leave a CommentKoen Verbeeck tries out a function:
I have data coming into my SQL Server database as JSON. Before I start parsing it which is quite intensive, I need to check if some values are present in the JSON. Is there a function I can use to do this? Let’s see what the new JSON_CONTAINS function in SQL Server 2025 can do.
Read on to see how it works.
Leave a CommentJeremy Schneider doesn’t wait for a response:
Postgres database-level “synchronous replication” does not actually mean the replication is synchronous. It’s a bit of a lie really. The replication is actually – always – asynchronous. What it actually means is “when the client issues a
COMMITthen pause until we know the transaction is replicated.” In fact the primary writer database doesn’t need to wait for the replicas to catch up UNTIL the client issues aCOMMIT…and even then it’s only a single individual connection which waits. This has many interesting properties.
Click through for the pros and cons of this technical decision.
Leave a CommentSteve Jones says better late than never:
I hosted this month, late as it turns out, but we still had a few entries. Here’s a look at the blogs people published.
Read on for links to the half-dozen entrants this month, who talked about string parsing in SQL Server.
Leave a CommentRecently, I thought a database query in a plan was straightforward. It looked innocent until I noticed strange behavior. The deeper I dug, the more I realized many people might be running into the same issue with ORM queries.
Click through for a toy version of the scenario, as well as two common problems with ORM tuning: blind index acceptance (which, admittedly, is a problem with or without ORMs) and implicit conversion on filters.
Leave a CommentChris Barber provides a primer on the types of keys that are critical for a star schema:
Keys are a core component of star schema modelling; relationships between tables are built using the keys. This article covers:
- The main key types
- Star Schema diagrams
- Best practices when using Keys
An understanding of keys become increasingly important with more complex solutions. Not only do you need to understand them from a modelling perspective, but a common vernacular is required to communicate with team members.
It’s easier to think of the keys Chris describes in two separate classes rather than four unique items. Surrogate and natural keys are descriptors of a primary key (or any other unique/alternate key), after all.
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