Nice overview. Loved mongo for very simple document storage where there is little to no need to do any complex joins. It can become a beast when needing to use the aggregation pipeline and transformations I've walked into that a couple of times now and wished I'd have stuck to something more relational. My own fault and lesson learnt 🤣 again though really nice overview and covers so many use cases.
The document data of MongoDB is like JSON (plus has more types) and it includes complex types like objects and arrays, often nested to multiple levels (upto 100 levels is possible as per the docs). Working with these complex structures is not always easy. First, the aggregation pipeline syntax is unlike other database querying syntax and there is a learning curve. Attempting aggregation queries on complex data and complex operations without proper learning, the tools and experience is not uncommon - it can create disappointments.
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Nice overview. Loved mongo for very simple document storage where there is little to no need to do any complex joins. It can become a beast when needing to use the aggregation pipeline and transformations I've walked into that a couple of times now and wished I'd have stuck to something more relational. My own fault and lesson learnt 🤣 again though really nice overview and covers so many use cases.
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The document data of MongoDB is like JSON (plus has more types) and it includes complex types like objects and arrays, often nested to multiple levels (upto 100 levels is possible as per the docs). Working with these complex structures is not always easy. First, the aggregation pipeline syntax is unlike other database querying syntax and there is a learning curve. Attempting aggregation queries on complex data and complex operations without proper learning, the tools and experience is not uncommon - it can create disappointments.