NoSQL Databases and Usage of MySQL as Enterprise DB


There is a fundamental shift in database management over the last several years, which is now moving from the relational DBMS approach to non-relational database management. Even though the users are not fully convinced about NoSQL usage as the non-relational DBMS, there are many advantages these can offer in modern-day enterprise database management as big data and machine learning applications etc.

As we know, relational DBMS were so strict in terms of data format, storage mechanisms, and concurrency controls. The dominance of SQL DBs is, however slowing down lately. For the startups and SMEs, NoSQL is now proving out to be a bit troublesome to use but offers a significant advantage in terms of scaling up. NoSQL also seems to be a highly affordable option for small businesses to adopt and scale up and down easily based on timely needs.

More about NoSQL

NoSQL is defined as Not only Structured Query Language, which means that while you plan to design an enterprise application or website, there are various many alternate mechanisms to be made use of. In the beginning, NoSQL was used as just a hashtag as #nosql, which was then finalized as the representing name of the new-gen databases without the need for SQL for data management. The major benefit for enterprises shifting to NoSQL is its Polyglot Persistence. Primarily, NoSQL DBs are:

  • DBS not using the traditional relational database model.
  • Primarily open source.
  • Run-on clusters
  • No schema (schema-less)

Startups using NoSQL

We can now see that the application developer is confused with the mismatches between relational and in-memory data structures. With NoSQL, developers can be more confident and comfortable about developing enterprise applications without being worried about the in-memory structures. Another alternate movement towards using databases is some specific integration points that encapsulate the DBs in enterprise applications and offer it as a service.

The modern concepts as infrastructure as a service contribute further towards a fundamental shift in DBMS terms with the need to support really big data volumes running on clusters. The relational DBs are not ideal to efficiently run on these clusters. Considering the needs of the previous web applications against the new-age applications, the need for storage for the ERP applications has grown multifold. The data management needs also diversified. NoSQL can meet these growing needs.

Advantages of NoSQL

Here is a quick overview of NoSQL advantages in enterprise database administration.


  • NoSQL can handle huge volumes of semi-structured or unstructured data too apart from structured data.
  • It can easily handle agile sprints, and continuous code pushes.
  • NoSQL supports object-oriented programming, which is more flexible and easier.
  • NoSQL model is much cheaper, and the architecture is simpler compared to the SQL architecture.

For consultation regarding NoSQL DBs for your enterprise database systems, you may contact expert DBAs of

Usage of MongoDB

MongoDB is one of the most popular NoSQL DB, which is an open-source and document-centric model. MongoDB follows a non-SQL query language, which is powerful and also MongoDB also does not function in the old model of database tables with columns and rows. It follows a different architecture that is primarily based on documents and document collections.

The primary unit of NoSQL is the data unit that consists of a key-value pair. It will let the documents to carry different fields and structures. With this, MongoDB also follows a specific BSON based storage format, which is a binary system based on JSON. The MongoDB data model is more elastic and combines different sets of data of multivariate types. It also does not compromise on the data access, indexing options, and validation rules. This will help reduce any downtime while trying to modify your data schemes.

Architecture of MongoDB

MongoDB primarily acts as a data container. Each of the databases inside the container has a custom set of files. A collection is a group of documents in MongoDB. In relational databases, a collection is a group of tables. In MongoDB, you can find different documents featuring different fields, but all these come from a specific collection. Document in MongoDB is a set of key-value pairs, which are connected with dynamic schemas. This model’s major benefit is that every document in the document collection may not have the same structure of fields. The common fields in the document collection may have different types of data. In terms of queries, there are both document-based and ad-hoc queries which are supported.

Unlike the conventional relational DBMS, we can also find any field index in the document. In terms of replication, MongoDB also supports master-slave replication. The MongoDB can work on multiple servers and can also run simultaneously. Data can also be duplicated during any hardware crash. Sharding also facilitates effective load balancing. As there are many replicas, better failure handling is also possible with MongoDB, which ensures effective protection against machine failure, rack failures, and data centre failures.

As we have seen, MongoDB follows a non-relational model.  MongoDB is document-oriented whereas the RDBMS is row-oriented. MongoDB follows a collection-oriented model, whereas the relational databases follow the row-oriented model.

Considering all these factors, we can see that MongoDB has far overcome many of the relational DBMS shortfalls. As many enterprises are looking to upgrade their DBMS systems to accommodate the changing database management needs, scalability comes up as a major consideration lately. Here, MongoDB offers exceptional scalability capabilities and makes it easier for enterprise users to fetch data and ensure automatic integration. MongoDB also has no downtime during application scaling.

Unlike the relational SQL databases, MongoDB stores data in JSON-type documents that are highly flexible and can make data more persistent. The objects in the applications are mapped with a document model, making it easier to work around with the data. Along with the developers, the operation teams can also perform their tasks better as MongoDB offers cloud service support. The cost of managing MongoDB is also reduced with commodity hardware. All these makes MongoDB an ideal choice for modern-day enterprises.

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