NoSQL (Interpreted as not only SQL) database is a non-relational and large distributed database system that enables the data for a rapid and ad-hoc organization and analysis of large data volume and disparate its data types.

NoSQL databases sometimes also referred as cloud databases, non-relational databases and Big data databases and their applications.

NoSQL database is generally referred by the Big Data companies to store a large number of databases. But as we know every technology has its good part and bad parts. So, now we will try to see the bad parts of the NoSQL or NoSQL Databases disadvantages or NoSQL Database Bad Parts below:

1. Lack of JSON:

This is first and main of key NoSQL Database bad parts, If you trying to use the NoSQL database to make the project then in that you will face many problems to use JSON.

Solving normalizations and data representation issues increases brain development for the engineers so in this case, engineers try to use the JSON is the development but with NoSQL, you literally can’t use the JSON so this is the first bad part of NoSQL.

2. Backup of Database:

This is second main of key NoSQL Database bad parts, Backups is the drawback in NoSQL(considering MongoDB) like incremental,differential e.t.c. MongoDB has mongodump tool for taking backup and restore but this tool is not yet mature like PhpMyAdmin, MySQL Workbench, Sequel Pro, HeidiSQL, SQLWave in MySQL.

MongoDB Backup

mongodump --host mongodb1.example.net --port 3017 --username user --password pass --out /opt/backup/mongodump-2013-10-24

MongoDB Restore Backup

mongorestore --dbpath <database path> <path to the backup>

mongorestore --host mongodb1.example.net --port 3017 --username user --password pass /opt/backup/mongodump-2013-10-24

Mongodump can take backup for an entire server, database or collection, or can use a query to backup just part of a collection

3. Standardization and Open Source:

NoSQL is an open source you can consider it as its advantage or disadvantage. The truth is, there really aren’t many reliable standards for NoSQL databases till date in the market, meaning that no two databases are likely to be created equal in terms of standardizations and performance. Support could end up being spotty when compared to a more traditional database implementation.

4. Lack of Maturity:

Compared to old relational database NoSQL database is still quite immature in front of SQL. This is also reflected also in lack of developers and administrators with the core knowledge and skills in that, in other hand NoSQL may be administrator and developer friendly but it will be nothing if there is no administrator or developer handling tools or understanding to address it. Available GUI mode tools for access the database is not flexibly available in the market.

NoSQL doesn’t have mature functionality like Group, Join (Inner Join, Outer Join, Inner Join, Cross Join), Table and Row Locking (Transaction Processing – Rollback, Rollforward, Deadlocks) etc.

Also, It doesn’t provide functionality or mechanism like Stored Procedures and Triggers as comparing SQL. in MongoDB we can create and store JavaScript function on the server in the special collection called system.js to reuse JavaScript function. The function can use the db.collection.save():

db.system.js.save(
{
   _id : "myCustomFunction" ,
   value : function (x, y){ return x + y; }
});

5. Consistency:

Because of the way data stored in the NoSQL data consistency will play the vital role to make the data consistent in all way.

NoSQL puts a scalability and performance first but when it comes to a consistency of the data NoSQL doesn’t take much consideration so it makes it little insecure as compared to the relational database.

6. Narrow Focus:

NoSQL database has very narrow focus as compared to the SQL. They are generally made just to store the data and have very less functionality as compared to the SQL like modification with the data, edit and delete all etc. that some functionality you will not get with the NoSQL.

When transactions enter the database, relational databases are still the better choice as compared to others. Further, NoSQL doesn’t really do so well with data backup automatically.

7. Removal of Duplicate Data:

Removing duplicate data means normalization of the data. This mind-blowing data you will get with Relational database i.e SQL but when you come with NoSQL it doesn’t have this feature means when you will try to enter the same query with same data it accepts but with SQL its not like that. So, in SQL it also helps to save the data and the memory storage.

In the Last word, NoSQL databases bad parts have gained the great popularity in last several years, with the popularity of big data and other features of the cloud.

While the technology is great for dealing with many features for dealing with unstructured data and its maintenance. it’s nevertheless limited in a number of another key area.

An administrator must thus consider carefully which type of database best suits their needs before committing to one implementation or the other for the software and its needs– the wrong choice could have disastrous consequences software.

Conclusion: Understanding NoSQL Database Bad Parts in 2025

In 2025, it’s more important than ever to understand the NoSQL Database bad parts before making architectural decisions. While NoSQL databases provide great flexibility, scalability, and performance for certain workloads, they also come with trade-offs. Issues like eventual consistency, limited querying capabilities, poor support for complex transactions, and increased developer overhead can create serious challenges if not properly managed.

By recognizing the NoSQL Database bad parts, developers and teams can make more informed choices—whether that means optimizing how they use NoSQL or choosing a more suitable data solution altogether. The key is to align your database choice with your app’s actual needs, not just the latest trends.

In this Article, we will first demonstrate that what these both things are i.e MySql and MongoDB because MongoDB is little new so we have first read about its definition.

MySQL Database:

MySQL is an open source relational database management system (RDBMS) which is based on Structured Query Language (SQL).

MySQL virtually runs on all platforms like LINUX, WINDOWS, MAC etc. MySQL is most often associated and used with the most web applications and open source system like the LAMP. Now the MySQL is covered by the ORACLE from 2008.

MongoDB Database:

The NoSQL is the replacement of the 40 years old relational database management system to use with modern web application development and also on all web applications increasing number of demand also the headache of the developers so they got the option to handle all things like Big User, Big Data, Cloud Computing and internet things with the MongoDB which is example of the NoSQL.

Difference between the MySQL and MongoDB:

In this part we will discuss the key parts of the differences between these two databases:

1. SQL databases are the table based databases means it stores the data in the row and column based format whereas the NoSQL stores the data in the document format like in the key-value format or graph format.
2. If the number of user’s data stored in the MySQL then it takes much time to response in other hand MongoDB does not take much time as compared to SQL to respond effectively.
3. For the big data storage, SQL is less preferred language as compared to MongoDB because it stores the data in key-value pair format so the execution time is also very fast.
4. MongoDB stores the data in the JSON format so it gives the results in the well-structured format with more flexibility and superior read and writes format.

Is MongoDB always Perform better than MySQL?

This is another classical question which you developers coming across, but this questions just to answer with YES or NO? Do you think that just saying this will be good for the 40 years old database and say yes to just a few years of the database? We will try to find out this here after searching for many things.

MongoDB is getting very popular in the market because of its many features and it is database structure which it stores in JSON. But what the real thing behind this :

A. How does MySQL process queries?

The MySQL database was developed when the web application development was on the verge of its starting getting popular with the normal people so it has the very old technique to process the data and execute the data.

It does not use the multiple threads to boost the performance it means when you want to process the multiple queries to get the high-end result at that time it processes only some queries and rest keep as it is.

After the first several queries result from it process remaining queries. So it takes time to show the full result which if you will see according to the user’s points of view they will never like it.

B. How does MongoDB process queries?

The internal execution of the MongoDB is completely different than the MySQL. Here I will compare only one thing about these two just be careful on this point.

In MongoDB, all the queries are not processed simultaneously. This means that all the write queries which are sent to the MongoDB server will be queued. From this smart technique, the execution time is far much better than the MySQL.

Conclusion:

As I saw all the pros and cons or MySQL versus MongoDB Database about these two things we found that MongoDB is doing good in all aspects like in storing data, processing of data, executing the query etc.

So I can say that the MongoDB is the winner and MySQL is looser but every developer has its own circumstances and usage they may feel good and more comfortable with the MySQL. It all depends on your type of usage and what the technique you can use to more simplify your code.

MongoDB NoSQL Database Pros :

1. MongoDB Database is absolutely schema-less. It is one major advantage for the users that are doing installations like Security camera features in multiple numbers inessential. Also, when you have a flexible schema just like how it is in the case of MongoDB, then you can find it to be one of the rated best options meant for the Document Stores too. RDBMS can be of futile choice compared to the MongoDB here. Moreover, you have the ease to scale out in case of MongoDB NoSQL Database.
2. It is possible to use the replica sets here and identify the scale reading easily. Auto-balancing features are best used to assess the scale reads or by using the option of sharing. You can keep on be firing up new machines as there are least supervision or monitoring services needed in this case of deploying a MongoDB.
3. All you need to do is to add on more machines and add on more RAM as well to increase the overall efficiency of the set up as such. Expansion plans are so flexible and easily achieved when you are relying on something like MongoDB. It is not the same case compared to the peers in the business as such. You can add on to the distributions easily to the working set up when you are using the MongoDB.
4. It is possible to use the MongoDB for free of expenditure as you are to run it in Linux, in fact, it is ideal to be run on anything cheaper than that as a kit too. Based on the data value that you choose to select you can decide upon the consistency as you will have to mark it up. Hence, the best fastest performance can be easily achieved in that way when you resort to MongoDB.

Some of the cons related to MongoDB are listed below as well:

1. Each and every other document in case of MongoDB is stored with field names and hence the data sizes could be significantly higher over a period of time when you see the accumulation.
2. When you are doing something like querying process, then there is no range of possibilities of any flexibility in the approach as such when you compare with the premium best options of the other kind. There is no rigid support offered for the transactions in case of MongoDB.
3. Single document level support can be something limited for some type of atomic operations alone. Speed is not so fast or up to the expectations of many when it comes to data analysis or doing some kind of aggregations as such when you are resorting to MongoDB NoSQL Database.