Instilling a pause to the SQL era, nowadays, many NoSQL databases are coming into the limelight, which they can choose based on their needs for more flexibility and scalability. The data-intensive enterprises and developers need not have to be confined to a single database platform option anymore.

As we can see, the NoSQL wave was first adopted by some of the major industry giants like Amazon DynamoDB and Google, etc. All these brought in many practical solutions to real problems, and all these companies also realized that SQL is not competent enough to meet all their requirements.

They first tried by upgrading their hardware to be faster, but even when that approach reached saturation, they tried scaling out the existing RDBMS solutions with schema de-normalization.

Finally, they decided to go with the NoSQL databases, which helped curb this problem primarily. NoSQL databases can store data in a denormalized form and follow various data storage models based on the needs of the users, which we will discuss in detail in this article.

NoSQL DB Key Characteristics

As there is a significant mismatch between the data structures of in-memory DBs and the relational data structure of applications, there can be many problems faced by the application developers. However, using the latest NoSQL databases, the developer may no more convert their in-memory structures to the relational structure to store and retrieve it. They can also use it as an easy integration point for other applications.

Why consider NoSQL databases?

As we can see, the erstwhile relational databases are not designed in a way that they can run smoothly on clusters. The enterprise resource planning applications’ storage needs may be different from the needs of a social media application like Facebook or Instagram etc. With this in mind, many organizations handling big data are switching to NoSQL to enjoy the benefits of higher scalability, better speed, and also continuous availability.

NoSQL database features

1. Satisfying need for increased Speed

As the faster response is the need of the time, data has to be placed in the memory to be retrieved anytime. In such a case, there needs a rapid response time for which we have to go for databases that store data in memory. To speed up your database, you may communicate with the RemoteDBA experts.

2. Need for scale

As there is an increased number of database users and the data volumes that enterprises require are growing, organizations may need highly scalable databases based on the changing demands.

3. Continuous availability

Slow performance and downtimes can surely drive valuable customers away. So, for data-centered businesses, there is nothing worse than frequent downtimes. There is a significant difference between RDBMS’s scalability approaches with the master-slave architecture and the continuous availability, which is offered by NoSQL databases like Cassandra. Many of the NoSQL databases even guarantee zero downtime by maintaining redundant data copies, which is kept by spreading it across a cluster at multiple locations.

4. Less location dependency

The need for location independence is also crucial in the global information technology scenario, where the databases need to have the ability to serve the data requests quickly to various locations with minimum possible travel time. With the fundamental architecture of master-slave, relational databases may struggle to ensure faster read access at many locations.

However, the NoSQL databases are spread across various destinations, and the data is decentralized with cloud availability. This will ensure data availability even when a location goes down completely. For example, Adobe now runs on the Apache Cassandra Database, connecting two data centers, making sure that the customers can read or write data from the nearest location with increased speed. Also, the NoSQL databaseslike Cassandra may offer a highly flexible data model that can be stored easily in structured, semi-structured, or unstructured formats.

Switching from Relational to NoSQL database

Many applications are made in SQL, which cannot be with NoSQL without creating new applications and starting the process from the ground up. There are also many challenges related to rewrites of legacy applications.

Here, augmentation is a process of making existing relational databases to larger by adding some NoSQL components to this. The enterprise users often adopt this approach than changing the outgrown RDBMS but y taking advantage of the better availability features using the NoSQL components.The fundamental parts of their applicationscontinue to exist on the RDBMS, but many other functional components will be modified to use the NoSQL databases.

While thinking of upgrading to the NoSQL database, considering the CAP theorem, there may be only two properties out of the three that can be achieved in any typical database environment. Consistency is one fundamental requirement which we may have to give up for the other two. As RDBMS tends to follow the ACID (Atomicity, Consistency, Isolation, Durability) principle, it may not be easy to scale the RDBMS. The data stores may handle things like Queries, Concurrency, Transactions, Replication, Schema, Scaling, etc.

The scalability and performance are odd to each other, and increasing any one among these may decrease the other’s effectiveness. You may have to execute the same request set over the same dataset for improved performance with a shorter time and little resource usage. With this, you can also find a tradeoff between resource usage and the actual processing time. We can say that we may reduce the processing time by consuming more and more resources. It is true when taken the vice versa too. While considering the types of NoSQL data stores, you can find various options available that will provide data storage, which allows data storage. These have different store data in NoSQL as Key-Value Database, Column-Family Database, Document Database, etc. Even though NoSQL databases’ appeal is high in terms of scalability and performance, there are some drawbacks that you need to consider while planning for complete migration from SQL to NoSQL. For some conventional business enterprises for whom database applications’ stability is more critical with a lesser number of users accessing it, relational databases may be a better option. So, do a thorough evaluation of the database models against your enterprise database requirements to identify which database model will best suit your needs and objectives.

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