Thanks for the article.
How are you defining data-heavy applications? Is it an application that is receiving/processing/sending millions of data points per second or is it actually the one with a highly normalized database schema?
That's a good question.
I am referring to high no. of data points = high no. of fields / highly normalized schema.
Sorry for not being clear.
Thanks for clearing out.
It would be great if you can elaborate on the following point as well:
Remember that plain Rest API implementations are simpler
I intended to recommend GraphQL for databases that have many fields and/or relationships.
".. Since most of my services are data-heavy, I particularly like the fact that I don't need to maintain a dozen end-points".
GraphQL enables selective retrieval and that (for me) is a big plus.
Obviously I am not a good communicator :p
I would like to answer your second question in more detail and have updated the post!
Thanks for the great questions.
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Thanks for the article.
How are you defining data-heavy applications? Is it an application that is receiving/processing/sending millions of data points per second or is it actually the one with a highly normalized database schema?
That's a good question.
I am referring to high no. of data points = high no. of fields / highly normalized schema.
Sorry for not being clear.
Thanks for clearing out.
It would be great if you can elaborate on the following point as well:
I intended to recommend GraphQL for databases that have many fields and/or relationships.
"..
Since most of my services are data-heavy, I particularly like the fact that I don't need to maintain a dozen end-points".
GraphQL enables selective retrieval and that (for me) is a big plus.
Obviously I am not a good communicator :p
I would like to answer your second question in more detail and have updated the post!
Thanks for the great questions.