I have a user installable application the takes a 2-5 MB JSON file and then queries the data for metrics.  It will pull metrics like the number of unique items, or the number of items with a field set to a certain value, etc.  Sometimes, it pulls metrics that are more tabular like returning all items with certain properties and all their fields from the JSON.
I need help making a technology choice.  I am between using either Pandas or SQLite with peewee as an ORM.  I am not concerned about converting the JSON file to a SQLite database, I already have this prototyped.  I want help evaluating the pros and cons of a SQLite database versus Pandas.
Other factors to consider are that my application may require analyzing metrics across multiple JSON files of the same structure.  For example, how many unique items are there across 3 selected JSON files.
I am news to Pandas so I can't make a strong argument for or against it yet.  I am comfortable with SQLite with an ORM, but don't want to settle if this technology choice would be restrictive for future development.  I don't want to factor in a learning curve.  I just want an evaluation on the technologies head-to-head for my application.
You are comparing a database to an in-memory processing library. They are two seperate ideas. Do you need persistent storage over multiple runs of code? Use SQLite (since you're using metrics I would guess this is the path you need). You could use Pandas to write CSV's/TSV's and use those as permanent storage but you'll eventually start to bottleneck having to load multiple CSV's into one Dataframe for processing.
Your use case sounds better suited to using SQLite, in my opinion.
Should I use a SQLite database or Pandas for my application