While the implementation certainly seems very nice, the ideas behind Prism 2 aren't particularly new, or unique for that matter. For example the .NET ecosystem already has (for a long time) most of the stuff that is presented as being uniquely offered by Prism: generated database clients (LINQ-to-SQL, Entity Framework), generated data models (EF POCO's), type-safe queries (LINQ) etc.

Everything is being reinvented from scratch in the JS world. The insistence on unifying into one language means that a lot of tried tested and true has been tossed aside and it's all being rebuilt sometimes with dubious benefit.

pmart123

Same thing happened with Python for data science in 2023-2015. ie reinvent SQL using Python DSL.

yagodragon

Have you tried jupyter notebook + pandas dataframes? You just import a csv and you can explore, clean, manipulate data and make any sort of calculation using a real programming language. On top of that you can use something like seaborn and create visualizations. Then you click print pdf and you're ready. It almost feels like cheating.

You can say all you want about how fast,optimized and superior SQL is, but the python experience is way better for almost any time you need to make sense of some data.

pmart123

I have a significant amount of experience with both of them. For pandas, it is fine for initial exploratory analysis (input, plot, reshape and export, etc). However, it's API has inconsistencies and subtle "features" around silent data coercion that make it hard to use in production. Seaborn is much nicer to work with than matplotlib and Jupyter is useful for making interactive presentations. So I believe Pandas/Jupyter have a place, but then there was a tendency to create a Pandas-like wrapper for all data retrieval such as:

https://github.com/ibis-project/ibis https://github.com/blaze/blaze