Which database to use for storing machine learning data? I am currently storing my training data into HDF5 files and I want my team and I to switch for a database for two main reasons:

the data is not used only by me and the different datasets are stored in different folders at different paths etc so I want to create a single database containing all the data
we need to store a lot of metadata like hashes, insertion dates, ground truth (that may differ depending on the application) etc.

I don't know which database to use. My first thought would be something like mongodb which is not relational, but I wonder if there are databases specialized in deep learning training out there. I heard of SciDB but I am not sure what to think about it, and I searched for &quot;databases for machine learning&quot; in google scholar without success. That is why I am asking the question here.
Thank you in advance for your help.
I share here the results of my quick research:
I think I will create a mongodb database to store everything, because it is easy to use and accross the NoSQL databases it is the one my company knows best.
If you want to use a database, you may also consider things like parallel access, distributiveness of the database, resilience, etc.
I think more advanced solutions like shared filesystems, spark, hadoop, sciDB (in particular, sciDB seems specialized for analytics on arrays only) etc are good for data lakes and when we want to process ALL the data or a big part of it at the same time, per batch or through a pipeline for example. Therefore, I don't need it for now, and the simpler the best.