MySQL observability is essential in modern enterprises, whether you run a few critical databases or operate at massive scale. With the right real‑time monitoring, teams reduce MTTD/MTTR, avoid cascading failures, and continuously track workload health—CPU, memory, I/O, buffer pool efficiency, session contention, transaction/replication lag, error rates, and query latency. This Grafana monitoring template helps teams […]

MySQL HeatWave is a fully-managed MySQL database service that combines transactions, analytics, machine learning, and GenAI services, without ETL duplication. Also included is HeatWave Lakehouse, allowing users to query data stored in object storage, MySQL databases, or a combination of both. Introduction In the 9.6.1 release of MySQL HeatWave, Lakehouse now supports the _metadata_filename column […]

We have reached the end of our series on deploying to OCI using the Hackathon Starter Kit. For this last article, we will see how to deploy an application using Helidon (Java), the MySQL REST Service, and OCI GenAI with Lanchain4J. We use Helidon because it’s a cool, open-source framework developed by Oracle. It’s lightweight […]

The starter kit deploys a MySQL HeatWave DB System on OCI and enables the MySQL REST Service automatically: The REST Service enables us to provide access to data without requiring SQL. It also provides access to some Gen AI functionalities available in MySQL HeatWave. Adding data to MRS using Visual Studio Code To be able […]

In part 4 of our series on the OCI Hackathon Starter Kit, we saw how to connect to the deployed MySQL HeatWave instance from our clients (MySQL Shell, MySQL Shell for VS Code, and Cloud Shell). In this post, we will see how to connect from an application using a connector. We will cover connections […]

Let’s now see how we can connect to our MySQL HeatWave DB System, which was deployed with the OCI Hackathon Starter Kit in part 1. We have multiple possibilities to connect to the DB System, and we will use three of them: MySQL Shell in the command line MySQL Shell is already installed on the […]

In our earlier post, we unpacked the mechanics of MySQL HeatWave maintenance, the behind-the-scenes process that keeps your MySQL environments secure, stable, and optimized without changing your database version. We also touched on how Auto Minor Version Upgrades occur when a version reaches the end of its lifecycle. With this update, MySQL HeatWave introduces Configurable Maintenance Windows and Auto-Upgrade Controls, giving you […]

If you want to create a new application, test it, and deploy it on the cloud, Oracle Cloud Infrastructure provides an always-free tier for compute instances and MySQL HeatWave instances (and more). If you are a developer, it can also be complicated to start deploying to the cloud, as you need to figure out 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 …

Bridging natural language processing with semi-structured data brings both opportunity and complexity.

MySQL HeatWave GenAI’s NL2SQL feature shows how natural language can simplify data interaction — even for JSON documents. Yet, because JSON embeds both data and metadata within a single column, LLMs may struggle without explicit schema cues.

By creating well-structured views that reveal JSON’s internal organization, you can transform unstructured data into a relational format the model understands — improving both query accuracy and overall usability.

This approach highlights how MySQL HeatWave continues to evolve as a powerful engine for intelligent, natural language–driven analytics.

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