SQL database management was in practice for many decades now; however, NoSQL is the new hot buzz on air for the last few years. In fact, we can see that it is not a buzz anymore, but users find it more comfortable and usable with the fast-changing data management requirements. However, when we should ideally use MongoDB instead of conventional relational database management systems?
The NoSQL products in general and MongoDB in specific should be effectively used to meet the database challenges. Check the below case scenarios, and if you face any such challenge, one may consider the usage of MongoDB.
While expecting high write loads
By default, MongoDB prefers to have high insert rate and can handle volumes over transaction safety. So, when there is a need to handle huge volume data lines, but there is only lower value for each in terms of business, then MongoDB perfectly fits. However, you may not do this with high-value transactions recording or for those who need optimum safety.
To ensure high availability in unreliable environments
With MongoDB, it is much easier and faster to set the replicaSet, i.e., the server sets which act like Master-Slaves. More importantly, it is also very safe, instant, and automatic to run recovery from each node or data centers in case of any failover.
When the need is to grow big
You can trust MongoDB in terms of its scalability and data sharing capabilities. With conventional MySQL databases, scaling is much harder. A single data table in MySQL may fail to perform even when it reaches to 10 GB of data per table. Also, when you need to shard or partition the DB, MongoDB comes as an effective solution.
To handle location-based data
MongoDB features built-in location functions. You can easily find data relevant to a particular location much accurately and easily from the DB. This is very important for the modern-day analytics and e-commerce business administration etc.
When the data set is growing big, and schema is unstable
Adding more columns to existing relational database management systems may lock the database into some database or else create an additional load, which will downgrade the performance of other tables. This tends to happen when the size of the table rows above 1 GB. This may be troublesome for systems like billing, which need to handle many TB’s of data in a single table itself.
The advantage of MongoDB in such a scenario is that its schema-less and so adding another field anytime will not impact the old rows or documents. It can also be done instantly without tampering existing data sets. There is also no need for a database administrator for schema modifications.
When you don’t have a database administrator
When you don’t employ a DBA as a small business or so, you can surely consider MongoDB. It has great class persistency whereas the classes can easily be serialized to JSON, which can be stored AS-IS in the database. However, adopting this approach, you need to follow the best practices by knowing them at the first point itself if you want to grow big.
Many providers are offering to consult on MongoDB like RemoteDBA.com, which you can avail to custom weave your enterprise database management practices. Now as we know the features of MongoDB, let us further peep into some of the advantages and disadvantages of it. As it is a non-relational database, we may have to compare it with the conventional relational database management system to assess the advantages and disadvantages.
There are a lot of great features coming with MongoDB as its in-built capabilities when compared to relational databases.
We can see that MongoDB come as schema-less DB. It means that the users can store any type of data in separate documents. Unlike RDBM, this offers a lot of freedom and flexibility in terms of handling various types of unstructured data.
With MongoDB, it is possible to store large data sets by effectively distributing it into different servers. As there are multiple nodes, even when a single server is unable to handle big volume data, there will not be any failures. The technical terms used to denote this capability is ‘auto-shardings’ of data.
- Top speed
As we have seen, MongoDB is document oriented. It is much easier to access the documents through indexing. With this, MongoDB also offers instant query responses. Speed is much faster than RDBMS.
- High availability
MongoDB has advanced features like GridFS and replication etc., which help to enhance data availability anytime. In turn, MongoDB’s performance also is very high compared to RDBMS.
MongoDB is horizontally scalable, and this advantage makes it an effective choice of organizations of any size. When there is a need to handle a huge volume of data, you can effectively distribute it among several machines and instantly retrieve.
No technology is fully perfect or complete in the changing industry environments. MongoDB too has some limitations as we discuss below.
- Not supporting joins
Unlike RDBMS, MongoDB will not support joins. However, you can still use joins by manually adding the codes. However, there is a chance that doing it manually may affect performance.
- Large on memory
As MongoDB stores the key names for every value pair and also as there is no join functionality, data redundancy could be there, and it will increase memory usage.
- Limitations of data size
The typical document size of MongoDB cannot be more than 16 MB. This could be a restriction in some cases.
- Limited nesting
The document nesting cannot be done more than up to 100 levels. This also creates some restrictions when there is a need for higher nesting levels.
- Not matured
MongoDB is a new technology compared to the relational database models which exist for more than two decades now. So, it’s still at the infancy stage and may take more time to mature and become fully functional.
We have covered the usage, advantages, and disadvantages of MongoDB. Users need to decide whether to consider MongoDB as your enterprise database application or to go with the conventional RDBMS model based on the requirements in hand.