MongoDB is a comparatively new database in the NoSQL DBMS system, which is not adopted by many users as a flexible non-relational database system for business applications. Many want to consider MongoDB but are confused whether it is right for the needs of their applications. This decision; however, fully depends on the type of data you have in hand and what functions you have to achieve with the data.
With the increasing volume of unstructured data coming on to business platforms, NoSQL databases database are deemed to be an ideal solution for real-time data management and analytical capabilities. Based on the unique business needs of the users, MongoDB can be an ideal solution for you if your need is the same. Further, in this article, we will discuss the basic aspects of NoSQL database administration and how MongoDB is changing business database management in the big data era.
The role of MongoDB in database administration
As we had seen above, modern-day data is very vast and unstructured. Being big and much complicated, alongside big expectations business users have from it, storing, processing, and analyzing data is a real challenge. This has led to the evolvement of a new database administration concept of NoSQL. Unlike the relational structure of conventional SQL databases, document-based databases avoid the table-based database structure and arrange the data groups more logically.
As one of the top-rated NoSQL database systems, MongoDB is now admired for a few fair reasons. This is a major database component in MEAN stack of software development. MongoDB is an open source alongside being cross-platform compatible. MongoDB also has many built-in features which make it an ideal choice for business database management too. When there is a need for flexible data storage and quick access to data, MongoDB has some significant advantage over others.
Another major need for modern-day data management is to make real-time decisions on the go based on the data. Creating a data-driven tailor-made experience to the users is important. Comparing to the conventional relational database management systems, MongoDB has a significant advantage over other such databases in these aspects. More importantly, MongoDB is not limited to MEAN stack, but it is also compatible with them.Net applications, Java, and other development platforms. This mighty database is not used by many leading organizations too as ADP, MetLife, The Weather Channel, Expedia, and Bosch, etc.
When many of the elements of networked applications are supposed to seamless and fast, data management shouldn’t be a bottleneck. In such a scenario, MongoDB can effectively meet the data challenges which are almost impossible for the relational databases to fulfill. The major advantages of MongoDB are:
Ability to store huge data volumes
Data now has no structure. For the purpose of storage, relational databases require structured data. But for growing organizations, the types of unstructured data like customer preferences, past purchases, location, or even the social media behavior like Facebook likes are important. NoSQL databases have no limitations in terms of data structure and allow users to add various types of data in any format. As MongoDB is document-based, you can store any JSON-like data points at one place, and there is also a need to define the data types.
Get the most from cloud computing
In the big data environments of modern times, cloud storage is a highly cost-saving and quick solution. Cloud database management as provided by RemoteDBA.com lets the data to spread across many servers and enable users to scale up or down the storage easily. MongoDB is able to load huge volume data and give a lot of flexibility to the administrators. It also ensures the availability of data in the cloud-based environment, featuring built-in sharding and easy distribution of data across various servers.
Ongoing development and quick releases
The need for app development of modern times is like quick Agile sprints. There is also a need to make constant updates in the data structure whereas it is also unaffordable to have downtime between version releases. In the case of relational databases, modifying it may really take time. However, with the dynamic schemas of MongoDB, you can easily try new updates and fast release of it without any breakage. Unlike relational databases, there is no need to prepare data in advance, and anyone can incorporate any new data quickly and at a very lower cost.
Location-based operations and data analytics
If your need is to gather and make use of geography-based data, then MongoDB comes with built-in spatial functions which will let you effectively harvest data from specified locations and make use of it for the analytical processes without any need to run any complicated extraction procedures.
In-line analytics and reporting
Business analytics largely depend on unstructured data now. MongoDB can handle that sort of data from different silos to be seamlessly incorporated and get a real-time snapshot of the data.
Capitalize on the data from connected devises and sensors
This is the major need of IoT where you get sensor data from various types of interconnected sensors and devices. For conventional relational DBMS, it is a big challenge to absorb and utilize sensor data, whereas MongoDB is open to any type of data and can analyze it within the database itself and provide quick analytical output.
Even though it comes with a lot of innovative advantages in modern-day database management, MongoDB has a few disadvantages too to consider.
Not supporting transactions
To ensure scalability and performance, MongoDB ditched on exchanges. This approach retrains zones in which MongoDB can be effectively utilized, and you also require enormous denormalization in order to reshape information models.
Not supporting the join operation
As MongoDB’s document approach contains all that you need, there is no existing join. This is by keeping in mind that the goal is to increase the capacity and horizontally scale. Even though this is the case, you can try your join by initiative a number of queries.
We can find that MongoDB utilizes a record in the form of memory mapping and the Operating System handles storage. The database span is getting restricted by virtual memory. At any point when the information surpasses the limit, inclusions may fail with no warnings.
Considering MongoDB as your business databases management system, you need first to understand that each data environment is unique with a set of needs and limitations. No doubt that MongoDB is built with the new-age business challenges in mind, but it has a few limitations too based on some specific requirements of the time. So, you need to have a thorough assessment by weighing the benefits and disadvantages as discussed above against the need in hand and take a decision accordingly.