Computer Science XII

MongoDB Introduction to NoSQL

Like another database scripting/query languages such as SQL, MySQL, and Oracle, MongoDB also provides a high performance, scalability as well as availability for managing the database. MongoDB is one of the most accepted NoSQL database and stores data in a JSON structure. It is what makes Mongo DB so scalable as well as flexible. In this chapter, you will learn about the concept of NoSQL and its types and benefits.

What is NoSQL Database?

NoSQL can be defined as a database which is employed for managing the massive collection of unstructured data and when your data is not piled up in a tabular format or relations like that of relational databases. The term NoSQL came from the word non SQL or nonrelational. There are a wide variety of existing Relational Databases that have been unsuccessful in solving several complex modern problems such as:

  • A dynamic change in the nature of data - i.e., nowadays data are in structured, semi-structured, nonstructured as well as polymorphic in type.
  • The variety of applications and the type of data feed into them for analysis has now become more diverse and distributed and is approaching cloud-oriented.
  • Also, modern applications and services are serving tens of thousands of users in diverse geo-locations, having diverse time zones. So data integrity needs to be there at all the time.

Data residing in multiple virtual servers and other cloud storage (remote-based) in the cloud infrastructure can be easily analyzed using the NoSQL database management techniques and largely when the data set is in a non-structured manner. So, it can be said that the NoSQL database is intended to overcome the diversity of data, increase performance, modeling of data, scalability, and distribution, which is usually encountered in the Relational Databases.

Structured Data Vs. Unstructured Data

Structured data are in a proper format, usually text files or which can be represented in a tabular format. Also, such types of data can be smoothly represented in chart-like form, and data mining tools can be used to process them efficiently.

Whereas unstructured data are haphazard data formats (such as document files, image files, video files, icons, etc.) where structured data can be pulled out or mine from unstructured data, but this process usually takes a lot of time. Modern-day data generated from different applications, services, or sources are a combination of structured and unstructured both. So, you will need something to store such data to make your application work properly. NoSQL based languages and scripts can help in this regard.

Benefit of Using NoSQL Data

  1. High elastic Scalability: In the case of traditional database services, there is a limitation where DBAs have to rely on scaling according to the development requirement. It ultimately intends for database users or organizations to purchase larger servers to cope with the increasing data load. In those scenarios, NoSQL databases put forward a much easier alternative of scaling out - the database gets distributed transversely numerous pre-existing hosts. As the demand for data storage availability is increasing, scaling out as a virtual environment will offer an added economical alternative for hardware scaling.
    It is a challenge to scale RDBMS data to commodity servers as cluster servers, which can be easily controlled using NoSQL databases, as they are pre-programmed to achieve scale on new nodes. These hardware costs are also low, which makes data storage affordable.
  2. Valuable and reliable for big data: Each organization, application, and services are generating large amounts of data that need to be stored appropriately. It brings into focus the concept of 'big data,' which focuses on the "industrial revolution of data". Usually, this is not possible for RDBMS; it is not able to store unstructured data and different types and vast amounts of data. This is why organizations turned towards using NoSQL systems such as MongoDB or Hadoop to handle 'big data' volumes.
  3. Reduced dependence/trust in in-house DBAs: The most crucial drawback of employing powerful high-end RDBMSs is maintenance, which can probably be done by employing trained DBAs, and they have higher pay scales. DBAs (Database Administrators) are implicated in designing, installing as well as performing these RDBMS operations, making it virtually indispensable. But in the case of NoSQL databases, they are intended for less hands-on administration, having features like data distribution, simplified data models, auto management and fetching data using simple code, and auto-repairing of data. So, management and organizing of data can be done remotely also by remote-DBAs, which is less costly and more straightforward.
  4. It's cheaper: NoSQL databases are intended for utilizing inexpensive commodity hardware for constructing clusters of the server, which helps in managing huge data volumes and transaction of data. On the other hand, traditional RDBMSs systems want expensive storage and original servers; this means they pose a higher cost per volumes for storing the data.
  5. Agile data models: Traditional database systems usually give immense headaches for managing the changes in storage and operational architecture, particularly for the large production ones. In such a system, minor changes need to be monitored carefully. On the other hand, NoSQL database systems do not contain such limitations on their data-storage models. They are flexible for any type of changes in not only the genre of data but also the architecture of data-storage, allowing comparative agility like the addition of new columns with no significant alterations or breakdown.

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