MongoDB 等 NoSQL 与关系型数据库相比，有什么优缺点及适用场景？

MongoDB 应用场景?

Take MongoDB for example, sure it's an awesome solution for special situations but i could never figure out why so many people were using it by default. I thought I just didn't understand something, but then it turns out that basically a lot of people were just jumping on the bandwagon and using MongoDB where a normal relation db like Postgres would be more appropriate.

Firebase Vs MongoDB : Battle of the Best Databases 2019You are here:HomeDev & DesignFirebase Vs MongoDB : Battle…

In production environment, each shard is a separate replica set

client application always interact with the primary node

Optional. Builds the index in the background so the operation does not block other database activities. Specify true to build in the background. The default value is false.

records

_id is 12 bytes hexadecimal number unique for every document in a collection. 12 bytes are divided as follows − _id: ObjectId(4 bytes timestamp, 3 bytes machine id, 2 bytes process id, 3 bytes incrementer)

Duplicate the data (but limited) because disk space is cheap as compare to compute time.

Combine objects into one document if you will use them together. Otherwise separate them (but make sure there should not be need of joins).

These 12 bytes first 4 bytes for the current timestamp, next 3 bytes for machine id, next 2 bytes for process id of MongoDB server and remaining 3 bytes are simple incremental VALUE.

We've decided not to have a model for the BookInstance:status — we will hard code the acceptable values because we don't expect these to change

MongoDB Training

When you’re picking a data store, the most important thing to understand is where in your data — and where in its connections — the business value lies. If you don’t know yet, which is perfectly reasonable, then choose something that won’t paint you into a corner. Pushing arbitrary JSON into your database sounds flexible, but true flexibility is easily adding the features your business needs.

The BSON format used by MongoDB is limited to a maximum of 64 bits for representing an integer or floating point number, whereas the JSONB format used by Postgres does not have this limit. Postgres provides data constraint and validation functions to help ensure that JSON documents are more meaningful: for example, preventing attempts to store alphabetical characters where numerical values are expected. MongoDB offers automatic database sharding for easy horizontal scaling of JSON data storage. Scaling of Postgres installations has often been vertical. Horizontal scaling of Postgres is also possible, but tends to be more involved or use an additional third party solution. MongoDB also offers the possibility of increasing write throughput by deferring writing to disk. The tradeoff is potential loss of data, but this may suit users who have less need to persist their data.