In a recent post, The Quirks of Index Maintenance in Open Source Databases, I compared the IO load generated by open source databases while inserting rows in a table with many secondary indexes. Because of its change buffer, InnoDB was the most efficient solution. However, that’s not the end of the story. Evolution of the […]

“ Of course, in practice, no query optimizer is perfect and there will be edge cases where the way a query is written will impact its performance.”

Q1. What are your current responsibilities as Principal Member of Technical staff?

Kaan Kara : I am contributing as the tech lead for query execution in HeatWave. My main responsibility is implementing new features in HeatWave, maintaining its stability, and supporting our customers with their HeatWave-related use cases.

Q2. Let´s talk about improving database query execution time. The way a query is written has a massive impact on its performance, and developers often face hurdles in structuring them optimally. What is your take on this?

Kaan Kara : SQL is a declarative language. That means, in ideal terms, the database optimizer should produce the best …

Keep your MySQL database protected with beginner-friendly advice on user management and security! Learn how to create users, grant and revoke privileges, and safeguard your data using library-themed examples and practical tips. Essential reading for every data explorer eager to lock up their digital collection.

Announcing Vitess 23.0.0 # We’re excited to release Vitess 23.0.0 — the latest major version of Vitess — bringing new defaults, better operational tooling, and refined metrics. This release builds on the strong foundation of version 22 and is designed to make deployment and observability smoother, while continuing to scale MySQL workloads horizontally with confidence. ✅ Why This Release Matters # For production users of Vitess, this release is meaningful in several ways:

Subtitle: Schema design, embedding workflows, hybrid search, and performance tradeoffs explained.

Quick Recap from Part 1

In Part 1, we introduced the MyVector plugin — a native extension that brings vector embeddings and HNSW-based approximate nearest neighbor (ANN) search into MySQL. We covered how MyVector supports scoped queries (e.g., WHERE user_id = X) to ensure that semantic search remains relevant, performant, and secure in real-world multi-tenant applications.

Now in Part 2, we move from concept to implementation:

• How to store and index embeddings
• How to design embedding workflows
• How hybrid (vector + keyword) search works
• How HNSW compares to brute-force search
…

Discover how to use transactions in MySQL to keep your data safe and organized—just like a diligent librarian! This beginner-friendly post explains what transactions are, why they matter, and how to use them with easy library metaphors, clear SQL examples, and essential tips for database reliability.

Data masking lets you hide sensitive fields (emails, credit-card numbers, job titles, etc.) while keeping data realistic for reporting, support, or testing. It is particularly useful when you collaborate with external entities and need to share your data for development reasons. You also need to protect your data and keep your customers’ privacy safe. Last […]

MySQL 9.5 has been released, here is a list of the contributions we included in it. Thank you to all contributors!

On October 10th, 2025, we released MySQL 9.5, the latest Innovation Release. As usual, we released bug fixes for 8.0 and 8.4 LTS, but this post focuses on the newest release. In this release, we can see contributions related to Connector J and Connector Net, as well as to different server categories. Connector / J […]

Unlock the secret to faster data searches with indexes! This post introduces beginners to the power of indexes in MySQL, using friendly library metaphors and simple SQL examples. Learn how—and why—to create indexes, understand their impact, and keep your growing database running at page-turning speed.