https://www.youtube.com/watch?v=rRoy6I4gKWU
NoSQL databases came about because of the need to store very large amounts of data and the need to store this data and traffic access to that data on multiple servers. RDMS was designed to work well on a single machine, but there is only so far a single machine can be scaled vertically and you quickly hit the limits when dealing with the amount of data handled by companies like Amazon or Google. NoSQL releases some of the ACID (Atomicity, Consistency, Isolation, Durability) restrictions of RDMS database allow it to distribute across multiple data centers, but of course, there are some drawbacks to this. Let's go through a few topics and see for each type of data storage, the pros and cons for those topics
Queries:
In relational databases, there is no limit on the queries you can write. Complexity of queries include multiple joins across different relational tables in the same database, whereas this data is located and scaled vertically in the same location. NoSQL databases on the other hand because of their distributed nature need to be denormalized ahead of time, by either combining data modules into one view, or by writing map reduce functions whose outputs are maintained and updated as new writes enter the database. If you know what queries you want to do ahead of time, then you might find NoSQL to be fast, because mapreduce functions can compute in parallel.
Transactions:
Traditional relational databases prided themselves in supporting transactions where you can edit anything in the world within a single transactions. NoSQL distributed nature is again a factor here, as it can't gaurenttee atomic operations since it doesn't know where the data is stored. Google App Engine datastore gets around this issue by introducing entity groups, and supporting transactions within an entity group. It actually support cross entity transactions as well, but those transactions are limited to 5. So, if you can structure your data in entity groups, or deal with the limits of 5 entities per cross-transaction, then NoSQL and Google App Engine datastore would work fine, otherwise you want the ACID qualities of RDMS.
Consistency:
NoSql only gaurentees "eventually consistent" data
Scalability:
Obviously the reason for NoSQL in the first place, data can be stored on multiple data centers with no master, with the support of mapreduce functions to get the data that you need. RDMS databases have gotten better at vertical scaling however.
Management:
Because of the less restrictions, developers can find that their time to their first MVP is faster, because of the less overhead of setting up SQL database.
Schema:
Part of the setup for a SQL RDMS database is a schema, and managing changes in the schema can be complex. With NoSQL they don't have those limitations, making changes to schemas having a lesser effect.
