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.

The post Querying the Unstructured: Natural Language to SQL for JSON Data first appeared …

Having explored the innovative MySQL HeatWave technology that converts Natural Language into SQL (Ask Your Database Anything: Natural Language to SQL in MySQL HeatWave), our next article in this series, dives into a practical use case demonstrating how an AI DBA Assistant can significantly simplify your query generation workflow. In MySQL, there are 3 specialized […]

The post Let Your AI DBA Assistant Write Your MySQL Queries first appeared on dasini.net - Diary of a MySQL expert.

As databases grow, DBAs and developers often face a tough choice:
+ Keep historical data in production tables and risk slow queries
+ Archive it and lose fast access

With HeatWave, you don’t have to choose. You can archive old partitions, keep recent data in production, and still run lightning-fast queries across all your data.

The post Archive Smarter, Query Faster: Unlocking MySQL Performance with HeatWave first appeared on dasini.net - Diary of a MySQL expert.

Have you already tried to upgrade the MySQL version of your MySQL HeatWave instance in OCI that is deployed with Terraform? When you tried, you realized, I hope you didn’t turn off backups, that the instance is destroyed and recreated new! This is our current MySQL HeatWave DB System deployed using Terrafrom: And this is […]

HeatWave MySQL Database Audit brings powerful enterprise-grade auditing capabilities to the cloud, allowing organizations to monitor and track database activity for security, compliance, and performance optimization. With features like customizable filters, real-time monitoring, minimal overhead, and seamless integration with MySQL tools, it enables administrators to log critical operations, detect threats, and maintain detailed records for regulatory requirements. The audit system is easy to set up, supports granular activity tracking, and provides actionable insights directly through the SQL interface.

The post HeatWave MySQL Database Audit first appeared on dasini.net - Diary of a MySQL expert.

Efficiently loading CSV data into your MySQL environment is a crucial step for many analytical workloads, especially when dealing with the substantial datasets common in today's data-driven world. Both MySQL Shell's parallel import utility and HeatWave's Auto Parallel Load feature offer robust and effective solutions, each catering to slightly different needs and environments.

MySQL Shell's util.importTable provides a flexible and powerful way to import data from various sources, including local disks and OCI Object Storage, into your standard MySQL tables. It's a developer-friendly tool that offers granular control over the import process.

For those leveraging the analytical power of MySQL HeatWave, the sys.heatwave_load stored procedure, particularly with its Auto Parallel Load capabilities, simplifies the often complex task of getting data into the in-memory columnar store.

The post …

MySQL 9.0.0 has brought the VECTOR datatype to your favorite Open Source Database. There are already some functions available to deal with those vectors: This post will show how to deal with vectors and create our own functions to create operations between vectors. We will use the MLE Component capability to create JavaScript functions. JS […]

MySQL HeatWave 9.0 was released under the banner of artificial intelligence. It includes a VECTOR datatype and can easily process and analyze vast amounts of proprietary unstructured documents in object storage, using HeatWave GenAI and Lakehouse. Oracle Cloud Infrastructure also provides a wonderful GenAI Service, and in this post, we will see how to use […]

In MySQL HeatWave, the Database as a Service (DBaaS) offered by Oracle, Machine Learning is incorporated to provide database administrators (DBAs) and developers with an optimal experience.

Those tools are the Auto ML advisors like the autopilot indexing for example.

MySQL HeatWave is also an invaluable asset for Data Analysts, offering straightforward tools that streamline the process of creating predictive models through data training and scoring.

The Data

The data we are using is the Bank Marketing data related to marketing campaigns over phone calls of a Portuguese banking …

MySQL HeatWave is the MySQL DBaaS provided by Oracle in OCI and some other clouds. Compared to the vanilla MySQL, one of the key features of the service is that it allows you to run analytics queries (aka OLAP) very quickly using the HeatWave cluster. You can also run such queries on files using LakeHouse.

When we talk about analytics, we also think about data visualization solutions. In OCI, you can use Oracle Analytics Cloud.

In this article, we explore the procedure to establish a connection between Oracle Analytics Cloud (OAC) and a MySQL HeatWave DB instance within Oracle Cloud Infrastructure (OCI).

Deploying OAC

We consider that you already have a DB System up and running in OCI. The first step is then to deploy an Analytics …