Chief Data Strategy and Governance Architect at a tech services company with 51-200 employees
Real User
Top 20
Dec 19, 2025
Integration is always important regarding operating systems and these types of products, so being able to integrate and export or import from JSON structures is very critical. Sometimes that is a little complicated because of the sometimes hierarchical nature of JSON or XML data formats, which do not always match to how you can structure MySQL on Ubuntu as a third normal form. There are those sorts of things that sometimes get inexperienced people; it does not seem to make sense. For denormalization, if you are trying to analyze it only, there is probably a shortcut that I have seen in some tools that once you define the third normal form type of data, it kind of automatically comes up with a way of analyzing it, turning it into an automated pivot table without you having to design the pivot table. Those things would be good to get the analysis. Some of the analysis that I had to code from scratch in Python were really simple binomial algorithmic comparisons. Some of that could turn into AI functions. Instead of coding it directly, I could use normal language saying I want to analyze this data based on whether this company has good financial viability to extend a million dollars of credit for buying fuel around the world or whatever the parameter is. That is what I can see coming in the future, that somebody that does not know how to code or does not really want to spend the time coding could actually ask in natural language AI to come up with that. To some extent, I have done that more recently with ChatGPT anyway to come up with a piece of code that at the moment does not work perfectly, but it is still Python and gives me the basic framework to then make it work elegantly.
I have not seen too much of a response in terms of issues. Sometimes, if the indexing is not done very well, I have noticed slowness, but largely, it has performed pretty well. The only area where I would say I have seen potential for improvement is occasional slowness, but I cannot really attribute it to the product; it could also be the design of the database and the queries. I have not encountered any other significant challenges. The slowness that occurs at times has not yet been established whether it is due to the design of the database, the queries, or the underlying software itself. I cannot comment on that right now.
Developer at a financial services firm with 11-50 employees
Real User
Top 10
Apr 17, 2025
More robust databases would enhance MySQL on Ubuntu. While fast, MySQL on Ubuntu may not handle complex applications as efficiently as alternatives, necessitating more robust database capabilities.
MySQL on Ubuntu 22.04 LTS is a powerful RDBMS offering robust data management for enterprise applications. It provides a flexible environment for handling large databases with high availability and ease of integration.
MySQL on Ubuntu 22.04 LTS combines the reliability of an open-source database system with the stability of Ubuntu's latest long-term support version. This combination supports scalable applications, offering extensive support for high-performance queries and transactions....
Integration is always important regarding operating systems and these types of products, so being able to integrate and export or import from JSON structures is very critical. Sometimes that is a little complicated because of the sometimes hierarchical nature of JSON or XML data formats, which do not always match to how you can structure MySQL on Ubuntu as a third normal form. There are those sorts of things that sometimes get inexperienced people; it does not seem to make sense. For denormalization, if you are trying to analyze it only, there is probably a shortcut that I have seen in some tools that once you define the third normal form type of data, it kind of automatically comes up with a way of analyzing it, turning it into an automated pivot table without you having to design the pivot table. Those things would be good to get the analysis. Some of the analysis that I had to code from scratch in Python were really simple binomial algorithmic comparisons. Some of that could turn into AI functions. Instead of coding it directly, I could use normal language saying I want to analyze this data based on whether this company has good financial viability to extend a million dollars of credit for buying fuel around the world or whatever the parameter is. That is what I can see coming in the future, that somebody that does not know how to code or does not really want to spend the time coding could actually ask in natural language AI to come up with that. To some extent, I have done that more recently with ChatGPT anyway to come up with a piece of code that at the moment does not work perfectly, but it is still Python and gives me the basic framework to then make it work elegantly.
I have not seen too much of a response in terms of issues. Sometimes, if the indexing is not done very well, I have noticed slowness, but largely, it has performed pretty well. The only area where I would say I have seen potential for improvement is occasional slowness, but I cannot really attribute it to the product; it could also be the design of the database and the queries. I have not encountered any other significant challenges. The slowness that occurs at times has not yet been established whether it is due to the design of the database, the queries, or the underlying software itself. I cannot comment on that right now.
More robust databases would enhance MySQL on Ubuntu. While fast, MySQL on Ubuntu may not handle complex applications as efficiently as alternatives, necessitating more robust database capabilities.