![]() It's difficult to give an across-the-board answer as they really are all different and tackle things differently.įor MongoDb as an example, check out their Use Cases to see what they suggest as being "well suited" and "less well suited" uses of MongoDb. You really need to look at and understand what the various types of NoSQL stores are, and how they go about providing scalability/data security etc. NoSQL DBs often lack the ability to perform atomic operations across multiple "tables".My experience has been using RDBMS in conjunction with NoSQL for certain use cases. It doesn't have to be a 1 or the other choice.Often the query functionality for a NoSQL DB is limited. IMHO, complex/dynamic queries/reporting are best served from an RDBMS.NoSQL does not necessarily mean "data loss" like you infer. But again, depends on the NoSQL DB/configuration. Adding more nodes to replicate data to is one way to a) offer more scalability and b) offer more protection against data loss if one node goes down. NoSQL is used for Big data and real-time web apps. ![]() The major purpose of using a NoSQL database is for distributed data stores with humongous data storage needs. It's often very easy to scale out NoSQL solutions. NoSQL Database is a non-relational Data Management System, that does not require a fixed schema.MongoDB - you can essentially choose what level to trade off performance vs potential for data loss - best performance = greater scope for data loss. Using NoSQL doesn't mean you could lose data.So you would usually have a flattened, denormalized representation of your data. NoSQL typically favours a denormalised schema due to no support for JOINs per the RDBMS world.NoSQL is typically good for unstructured/"schemaless" data - usually, you don't need to explicitly define your schema up front and can just include new fields without any ceremony.It really is an "it depends" kinda question.
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