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This article is about how to analyze the quality of MongoDB. The editor thinks it is very practical, so I share it with you. I hope you can get something after reading this article. Let's take a look at it with the editor.

For people who are new to MongoDB, MongoDB is a NoSQL-type document database. The key-value pairs contained in the document constitute the basic unit of data in MongoDB.

But what is certain is that MongoDB is indeed the current NoSQL database. It is widely accepted and suitable for a variety of situations (although not all projects use it).

Based on my experience with MongoDB over the past few years, I will briefly introduce the advantages, disadvantages and ugliness of MongoDB.

Benefits

Since MongoDB became popular, its advantages should outweigh its disadvantages and ugliness. If not, developers will not accept it. Here are some good aspects of MongoDB.

Flexible data model

With today's dynamic user cases and ever-changing applications, having a flexible data model is a boon. A flexible data model means that there is no predefined schema, and documents can hold any set of values based on any key value.

Expressive query syntax

The query statement of MongoDB is very expressive and easy to understand. Many people would say that this is not like the SQL statement. But when we can move forward and query statements are simpler and more expressive, why do we insist on queries like SQL?

Easy to learn

MongoDB is easy to learn and quick to use. The basic installation and execution will not take more than a few hours. More powerful settings may be complex, but I'll talk about it later.

Based on the above features, it must be easy for you to incorporate it into your project.

Performance

Query performance is the strength of MongoDB. It stores most of the operable data in memory. All the data is solidified on the hard disk, but during the query process, it will not pass the data from the hard disk (that is too slow). It fetches data directly from local memory, so it is faster. Therefore, you can take advantage of the performance advantages of MongoDB by setting the correct index for the data and providing enough memory.

Scalability and reliability

MongoDB is highly scalable in the use of fragmented data. Horizontal scalability is a bright spot in most NoSQL databases. MongoDB is no exception.

It is also highly reliable because its replica set data is replicated asynchronously to more nodes.

Asynchronous drive

For all modern applications, using asynchronous non-blocking IO is the key to speed up. The MongoDB asynchronous driver supports the language of *.

Document

Having good documentation can make life much easier for developers, especially when they are dealing with new technologies. MongoDB has excellent documentation.

Text search

If you are building a website and need to search all your data, text search is essential. For example, an e-commerce site that uses a database with text search is more beneficial to users.

Server script

If you have operations that need to be performed on the server side rather than the application side, you can do that in MongoDB. Put the mongo statement in a .js file and execute the js file with the mongo command.

Document = object

The advantage of a document database is that objects can be stored as a separate document in MongoDB. There is no need for object relational mapping (ORM) here.

Shortcoming

We've seen all the advantages of MongoDB, and now we're going to talk about the disadvantages. I'm sure critics are more interested in this part. If used improperly, MongoDB may do bad things.

Nowadays, few applications actually need transactions, but there are some programs that do. Unfortunately, MongoDB does not support transactions. So don't use MongoDB when you need to modify multiple documents or collections in a request. Because there is no ACID guarantee, it may cause data corruption. Rollback operations must be handled by your application.

No trigger.

In a relational database, there is a trigger, which is very useful in many cases. But there is no such thing in MongoDB.

Storage

MongoDB requires more storage than other popular databases. The introduction of WiredTiger in MongoDB 3.0 solves this problem, but using WiredTiger is not ideal for most applications.

Disk cleanup

MongoDB does not automatically clean up disk space. So if the document is modified or deleted, the disk space will not be freed. You must release it manually or by rebooting.

Ugly

Sometimes ugliness can be worse than bad. It is important to understand the shortcomings of a technology before using it. It won't stop you from using it, but it can make your life very difficult.

Hierarchical structure

If you have a data model that recursively contains child data objects (for example, an object has child objects of the same data type and has many levels), the document structure of MongoDB will become very ugly. Indexing, searching, and sorting these recursively embedded documents will be very difficult.

Join (connection)

It is not easy to join two documents in MongoDB, and although MongoDB 3.2 supports left outer join (lookup), it is not yet mature. If your application needs to retrieve data from multiple collections in a single query, that may not be possible. So you have to make multiple queries, which may make your code look a little messy.

Indexes

Although MongoDB boasts speed is one of its highlights, it depends on you building the right index. If you build a bad index or a composite index in the wrong order, then MongoDB may be the slowest database.

If you have a lot of filters and sort fields, you may build a lot of indexes on a collection, which is of course a bad practice.

Duplicate data

You may have a lot of duplicate data, and MongoDB does not support relationships. It may be difficult to modify these duplicate data, and due to the lack of transaction support, we may also corrupt the data.

Conclusion

Summary, as long as you use it properly, MongoDB is an excellent database, otherwise it will cause you trouble. You will suffer from using it in an inappropriate place.

Careful analysis and consultation with experts. If you use it correctly, you will definitely love it.

As for the bad and ugly parts, you can use design patterns to solve some of these problems. I explained the MongoDB design pattern in my article.

The practice of MongoDB

Several MongoDB practices are listed below:

Hardware

Make sure your dataset can be put into memory

Use Compression

Each server runs a single MongoDB

Use solid state drives for applications that write more data

Data model

All the data of a record is stored in one document.

Avoid large documents

Avoid unnecessary long field names

Remove unnecessary indexes

Delete indexes with other index prefixes

Application program

Modify only changed fields

Avoid negative query

Run explain () for complex queries (see execution plan)

Use override queries where possible.

Use bulk inserts when needed.

Installation and configuration

Have at least one slave library and one quorum

The parameter write concern should be set to 2 when the data is very important

There are daily data dump backups.

The above is how to analyze the quality of MongoDB. The editor believes that there are some knowledge points that we may see or use in our daily work. I hope you can learn more from this article. For more details, please follow the industry information channel.

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