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Ocean of NoSQL databases. Which one is best for your Business Application



Today, most data is stored digitally. Most of the information on the internet is stored in some type of server or database, operated by different companies. For us to be able to use and manipulate this data, we need a medium that is convenient and accessible. SQL (Structured Query Language) is one of the earliest database management systems, streamlining the process of data collection, storage, and retrieval. The phrase refers to a decade-old paradigm that still exists today in the sheer variety and depth of database systems. There is growing interest in fundamentally different technologies due to the growing volume of unstructured data, the availability of storage and processing power, and the evolving analytic requirements.


As a popular alternative to traditional RDBMSs, NoSQL shows promise for a variety of modern applications.


What is a NoSQL Database?


In general terms, Databases, which store data in a format different from relational databases, are known as NoSQL databases. NoSQL stands for “not only SQL,” which pertains to the fact that either the database can store and manage data using “no SQL” at all or it can work in a combination that combines the flexibility of the newer approach (NoSQL) with the power of the traditional relational system (SQL).


Types of NoSQL Database


  1. Document Databases

  • The data in a document database is stored in JSON, BSON, or XML documents (not in Word documents or Google Docs, of course). Documents can be nested in a document database. For faster querying, certain elements can be indexed.


  • A document can be stored and retrieved in a form that is much closer to the data objects used in applications, which means less translation is required. When moving data between applications and storage, SQL data must often be assembled and disassembled.


  • Document databases are popular with developers because they have the flexibility to rework their document structures as needed to suit their application, shaping their data structures as their application requirements change over time. This flexibility speeds development because, in effect, data becomes like code and is under the control of developers. In SQL databases, intervention by database administrators may be required to change the structure of a database.


2. Key value stores

  • A key-value store is the simplest type of NoSQL database. Each data element is stored as a key-value pair consisting of an attribute name (or "key") and a value. A key-value store is essentially a relational database with only two columns: the key (such as "state") and the value (such as "Alaska").


  • Shopping carts, user preferences, and user profiles are examples of use cases.


3. Column-oriented databases

  • A column store is organized as a set of columns, while a relational database stores data in rows. If you want to run analytics on a small number of columns, you can read those columns directly without consuming memory. As columns are often of the same type, they benefit from more efficient compression, making reads even faster. Columnar databases can quickly aggregate the value of a given column (adding up the total sales for the year, for example). For example analytics.


  • Unfortunately, there is no free lunch, which means that while columnar databases are great for analytics, the way in which they write data makes it very difficult for them to be strongly consistent as writes of all the columns require multiple write events on disk. Relational databases don't suffer from this problem as row data is written contiguously to disk.


4. Graph Database

  • In graph databases, connections between data elements are captured and searched, overcoming the overhead associated with JOINing multiple tables.


  • Very few real-world business systems can survive solely on graph queries. As a result graph databases are usually run alongside other more traditional databases.


There is a vast ocean of NoSQL Databases available to us which poses a conundrum and can look intimidating to anyone who is new to the language and is looking to scale his business using the features of NoSQL. We have picked a handful of databases that we believe might be helpful for you if you are trying to integrate NoSQL into your business. They are :


5. DynamoDB

If your business is planning to launch a cloud-based product and has decided to use the Amazon web services you will be using products like LightSail or Amplify. DynamoDB integrates perfectly with those products.DynamoDB also encrypts all data by default, and backups of data can be easily accessed through the AWS platform. If security or data loss prevention is particularly important to your business then DynamoDB could be a great choice.


6. Redis

If your business or product is dependent on storing and retrieving data in extremely short timeframes, Redis is a great choice. Redis was developed in the C language and has the potential to operate quickly. Data does not need to be fetched from slower devices or be recomputed as it is simply retrieved from the user device’s cache. While this may not be possible for large quantities of data, it can give huge speed boosts for lower amounts of data.


7. MongoDB


It is a general-purpose document-oriented database. Since it is document-oriented, it is optimized for storing all of the information about different items in a single place, making it easy to access all of your data on a single topic. MongoDB has a horizontal, scale-out architecture which means it can handle huge volumes of traffic and data.


This makes MongoDB a good option if your business is expected to store terabytes of data, or the database is going to be accessed by millions of users. It is also very popular among startups as there is no need to change their database once their business has expanded significantly.


8. Neo4j


Neo4j is a graph-based database. This means that it is not only great at handling data, but also relationships between different data points. If your business makes use of a lot of social media or personal interest data, it would be very beneficial to have a graph-based database.


Another popular use case for Neo4j is in recommendation systems. If your business needs to recommend new content to users such as articles to read or videos to watch, it is important that the database can find related content.

There are many NoSQL Databases available we have only mentioned a very few of them and their uses. Hope this article has brought you some clarity and hopefully next time you decide to choose a database for your business needs it will be much easier.


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