MongoDB is one of the latest and advanced systems in data storage and management ecosystem. Even though it is not as big as the giants like Oracle, MongoDB had drawn a lot of attention in NoSQL DBMS with the models of a distributed key-value store, MapReduce calculation capabilities, and also the document-centered NoSQL data distribution.
The philosophy of MongoDB focuses more on retaining as many conventional functionalities even when permitting the horizontal scaling. This makes the developer’s and database admins tasks much easier and quicker. MongoDB sits between the most powerful yet inefficient RDBMS and the high performing but simple system of key-value stores.
MongoDB is very cool, but before opting in, you should consider whether it is the right choice for you in enterprise database management. This decision should be taken based on the needs of your enterprise applications and future goals. You should first know about what the benefits and disadvantages of MongoDB that there is nothing more unfortunate than building the entire application over a particular database and later identify it to be a wrong fit.
First, in this article, we are discussing some positives and negatives about MongoDB.
Positives of MongoDB
MongoDB is a non-relational database that is designed to handle big data well in terms of storage, maintenance, and querying for big applications like social networking. MongoDB attains this optimal performance ability by adopting the key-value model, which is easy to scale up. Unlike relational databases, MongoDB considers the document as the primary storage unit.
Scalability is another big advantage of MongoDB. Unlike conventional database management solutions, MongoDB is horizontally scalable. Which means, more machines get added as the traffic and data grows by keeping the availability and responsive speed to the optimum.
MongoDB also supports the feature of auto failover and auto-sharding etc. While the data on at one node reach to the fullest threshold, data gets automatically rearranged to another node for even distribution. From the application perspective, the cluster is considered as a single node, which remains largely scalable and highly transparent.
MongoDB document models also make the development much easier. Unlike its conventional counterparts, the document doesn’t follow the concept of rows, tables, schemas, and even the queries which are similar to the relational database. If you have used Solr or Lucene ever, then you can find that the document model of MongoDB is much similar to that of Lucene document. If you need to handle a lot of data in unstructured form, then following a document model is the ideal choice.
For big enterprise websites and social media applications, you have to deal with the website traffic, click stats, likes, following, etc. Frequently generated data like these will be huge and may have weaker relations to one another, so they don’t need to be fully consistent. In such a scenario, MongoDB can be the best choice to store and process such data. In real, MongoDB was developed by DoubleClick to track online advertising activities, which then got acquired by Google for serving the Adsense network.
MongoDB has no scheme. The document for data store may consist of any number of fields. In fact, you can dynamically add more fields to the existing documents also anytime. There is no ALTER TABLE required. MongoDB documents are simply like PHP arrays, JavaScript JSON, Python dictionaries, or Clojure maps, which makes it much easier to communicate with MongoDB using dynamic languages like PHP, Python, or JavaScript.
MongoDB is also able to represent rich data models using BSON format. As RemoteDBA.com points out, this feature makes an agile development model possible. Unlike relational database models, JSON data seamlessly fit into an OOP model, which almost all programming languages support. In the DB models, you need the ORM framework as Hibernate to deal with mismatches between the OOP and the relational databases. MongoDB also effectively supports a very safe mode what ensures the insertion successfully.
Negatives of MongoDB
MongoDB doesn’t support transactions. In order to achieve maximum scalability and performance, MongoDB tends to ditch transactional support. MongoDB easily scales horizontally and utilize cheap hardware for load balancing. Horizontal scalability is a hard task generally in case of relational databases. However, for NoSQL databases like MongoDB, it’s a breeze, but at the stake of transactions.
The relation between various datasets is weak even when MongoDB is the best choice to handle a lot of data, i.e., big data. The actual initial purpose of MongoDB was to handle a live stream of many independent events, like recording the clicks on online ads. However, it may not be the right fit for the stronger related data as financial transactional information, i.e., if there is a need for money transfer from a bank account, there are a lot of related records to be modified simultaneously. RDBMS may handle this with the help of transaction.
However, in order to overcome this flaw, MongoDB now supports some operations like the atomic decrement and increment and findAndModify, etc. In MongoDB, modification to a single document remains atomic, but the operations which involve various documents are not handled in the atomic model. So, the ideal practice is that you must try to store as much information as possible in every single document to avoid spreading of data into multiple documents. In the relational model, this approach is known as renormalization.
MongoDB doesn’t support the join operations. As the document consists of everything needed, MongoDB has not to need to have joined. However, this too is a major trade-off of MongoDB to attain its ability to scale horizontally. However, it is possible to perform in MongoDB by making multiple queries. MongoDB also uses the memory-map for files and allow the OS to handle caching. The database size is limited by the virtual memory offered by the OS and hardware.
To conclude, we can say that MongoDB many features compared to the relational database as join or transaction, but it can scale up horizontally easily and also use a schema making it so easy to manipulate with the JSON type of data format. When used properly, MongoDB is a very powerful tool, but it may not be a one-size-fits-all type of solution.
