MySQL
How easy is it to use the VillageSQL MCP extension?
VillageSQL published Access MySQL over MCP with vsql-mcp . The extension serves the Model Context Protocol from inside the database, so an agent talks to MySQL over Streamable HTTP without a sidecar holding a credential.
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Getting VECTOR capabilities in MySQL 8.4 using VillageSQL
For this quick verification of the 0.0.7 development branch of VillageSQL with the new vsql-vector plugin. Recreate the VillageSQL Percona Live presentation using MySQL version 8.4 and SVECTOR. Demonstrate a more detailed example using SVECTOR(1024) string embedded data.
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Why INSERT IGNORE should not be used
Let’s say you’re building a reference table from source data, e.g. a silver medallion table from a primary source. In this example I am using a file of random locations on the globe extracted from OpenStreetMap (OSM) as my primary source.
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Curated MySQL Data Sets for Realistic Testing
Synthetic benchmarks have their place, but I have always preferred working with real data. Not client production data — that stays private — but publicly available datasets that reflect the messy shapes, skewed distributions, and indexing challenges you encounter in the wild.
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COSCUP 2026: Planning your upgrade to MySQL 9.7
I recently had the pleasure of presenting Planning your upgrade to MySQL 9.7 at COSCUP 2026 in Taipei, Taiwan. COSCUP (Conference for Open Source Coders, Users and Promoters) is one of the largest open source conferences in Asia, and the community there is always engaged and technically sharp.
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A first look at MySQL 26.7 Early Access
MySQL has dropped its newest release , categorized as “Early Access” and available at https://labs.mysql.com/ . While this post is not going to go into depth, I wanted to at least validate the management changes you verify between normal MySQL upgrades.
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VillageSQL Extensions with versioning
VillageSQL has just released it’s latest version 0.0.5 , describing this as stable release for installations with full MySQL 8.4.10 compatibility. With my primary work around extensions, specifically vsql-statistics , I took the new versioning features for a test.
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Producing IQR and Outlier statistics with SQL
The interquartile range (IQR) measures the spread of the middle 50% of a distribution — the distance between the first quartile (Q1) and the third quartile (Q3). Combined with Tukey’s 1.
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Producing Mode statistics with SQL
The mode is the value or values that appear most frequently in a dataset. Unlike the mean or median, it applies naturally to categorical and ordinal data — star ratings, product codes, survey responses — and reveals what is most common, not what is average.
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Extending MySQL Capabilies with UDFs, Plugins and Components - Part 2
MySQL offers three different approaches to extending the SQL capabilities with the default product you download and install. These are: User Defined Function (UDF) MySQL Manual MySQL Plugin MySQL Manual MySQL Component MySQL Manual In my prior post I provided a new uuidv function that accepted a numeric argument to return a string of the version of UUID specified.
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Producing Alternative Means statistics with SQL
MySQL’s built-in AVG() computes the arithmetic mean — the sum divided by the count. That is the right default for many questions, but it is not always the right measure of central tendency.
Read moreExtending MySQL Capabilities with UDFs, Plugins and Components
MySQL offers three different approaches to extending the SQL capabilities with the default product you download and install. These are: User Defined Function (UDF) MySQL Manual MySQL Plugin MySQL Manual MySQL Component MySQL Manual For the purposes of this post I will be using the current LTS version MySQL 8.
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Producing One-Sample Z-Test statistics with SQL
The one-sample Z-test determines whether a sample mean differs significantly from a known population mean when the population standard deviation is also known. It is the appropriate test when the population parameters are established — quality control benchmarks, national averages, long-run process measurements — and you want to evaluate whether a new sample is consistent with them.
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Switching to JSON Error Logging in MySQL
You no longer need to manually parse the MySQL Error log via scripting and RegEx pattern matching. Using the component_log_sink_json component you can obtain JSON error logging for easier parsing.
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