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MySQL suits organizations of any size, in any industry, including Enterprise and SMB across Web & E-commerce, Financial Services, Healthcare, Retail, Telecom and More.
Open-source machine learning solution for enterprises that helps businesses by managing digital advertising, claims management, fraud detection, advanced analytics, and more.
Overall, my experience with MYSQL has been great. This is a very reliable and efficient software, and is very popular throughout the industry owing to its features and stability.
With huge data, I had faced data loss and improper data retrieval but it is very rare and manageable. Some of the error messages are so general and unable represent the actual problem.
I like the security it provides for the users. And i am happy with the ability of portability of the data with the secondary databases.
I think the main downside for me is that the software is not that intuitive. I struggled a bit and it demanded some research to get used to it.
It was recommend by my friend and he said that it is very fast and reliable data base program but also it is very simple to understand and work with it. There for I choosed it and he said true.
This i a known well-issue, and there is no cure at this moment, you have to reboot the database instance. This is simply a disaster.
The recent upgrades to allow JSON fields has been wonderful. Also Amazon's version "Aurora" is awesome.
The version update is bad it should have an automatic update and to use in the HTTPS url for example just internally messing with his code.
The major benefit of the product in the AutoMl. It's really useful when you are trying to optimize the parameters.
Lack of management and no accountability. It's hectic and unorganized to the point where you'll have no idea what you're doing, and what you should be doing.
It is really fast and run on really low memory like 2 GB. I have learn lotta new information about ML and deep learning thanks to H2O's help buttons.
Programmatically using the software is difficult because the documentation is lacking and it is hard to find the documentation that they do have.
Most of the ML algorithms are supported and available to use. It's easy to launch H2O from R and it noticeably increases the speed of algorithms and reduces time.
Notebook has its own shortcomings, which some operations seem less convenient. For instance, if the error output is too lengthy, I have to scroll all the way up to get where I need edit the code.
Notebook's nature of keeping things in one place. Some nice build-in features to interact with different data resources.
There is no feature engineering. Depending on your data size, H2O.AI can take up lots of memory.
Samuel S.: Hi, my name's Samuel. I'm a director for a website design company, and I recommend MySQL. I'll give it a five out of five, and if you want to see more reviews like this, click the link below. Before using MySQL, I used to use Excel for my data. I used to store my data like that, but I needed a more reliable, more accessible way to get connected to my data, so I decided to use MySQL, which is great. I really like using MySQL, because my data is all in a central location now. It's very secure, as well, and it allows me to have more than one user connecting to the database, and not only that, more than one application, as well, so it can be a single source of truth information, which is what I really like about it. The initial setup is somewhat advanced. I used sort of other tools to set it up. I used WordPress, which installs and sets it up for me. The install and setup is relatively easy, but you can get more advanced when you're doing your own queries into the database itself. There're a lot of database applications out there, but I think MySQL is one of the highly rated ones. A lot of the larger organizations use it, because it's really reliable and secure and safe.
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