NoSQL as the New Magnet in the Global Big Data Movement

NoSQL is the latest in database technologies, evolving over many years and now taking up the web world by storm. Big Data and Cloud Computing experts now mostly use NoSQL DBs to scale out seamlessly. We can see top-notch internet companies like Google, Facebook, LinkedIn, and Amazon, etc. rely on NoSQL. By overcoming the shortfalls of the relational databases, NoSQL is proposing many innovative solutions to the database users and administrators.

The primary issues with data had always been two-fold: finding cost-effective solutions to store ever-increasing data volume and finding more innovative ways to mine the information to derive meaningful business intelligence insights. Relational database management systems were not the best solutions for all the given use cases as those were not able to accommodate the rising volume of unstructured data.

When the needs for data storage and quick processing needs started to grow exponentially, NoSQL stands up high as a cloud-friendly DBMS, which puts forth a dynamic approach to storing and processing unstructured data quickly. Many heated discussions are going on in the IT industry about the benefits and demerits of NoSQL over SQL. Still, the fact is that there is an increasing number of users moving to NoSQL, which is proving to be the new magnet of Big Data movements.

What is NoSQL?
When people say "NoSQL DB," they refer to it as non-relational databases. Other variants of NoSQL expansion are "non-SQL" and "not only SQL," etc. Whatever the case is, everyone agrees that unlike SQL DBs, NoSQL databases can store data in any given format. However, there is also a misconception that NoSQL databases exist as non-relational databases, which may not store the conventional type of relationship data.

The fact is that NoSQL databases can also store relationship data, but the only thing is that related data is stored in a different form than SQL in NoSQL. Compared to the SQL database models, many users find the NoSQL relationships much easier and more flexible than SQL as the related data in it will not be split between various tables. NoSQL data models also let the associated data to get nested effectively in single data structures.

With the introduction of NoSQL databases towards the end of the first decade of the 2000s, the cost and overhead of database management mainly decreased. Also gone those days when we needed to create a very complicated and severe to handle data models to limit the scope and overhead of data duplication. Rather than storage, most of the time, in the case of conventional SQL, developers were becoming a higher cost in terms of enterprise application management. NoSQL databases also helped to optimize developer productivity too.

As the cost of storage started decreased rapidly with SQL, the count of such applications that needed to store big data and query those increased. Data started popping in every shape and size as structured, unstructured, semi-structured, and polymorphic data, etc. Defining the schema, in this case, is nearly impossible, whereas NoSQL let the developers to efficiently store substantial unstructured data volumes without schemas, by enjoying a lot of flexibility.

For those who look for cloud computing and remote database administration services, RemoteDBA.com offers apt cost-effective choices for the same. Now let's explore the significant differences between NoSQL DBs vs. SQL and the key takeaways.

The significant differences: NoSQL vs. SQL
For about 40 years, SQL remained the front, back, and center of database administration. SQL allowed to build some powerful queries to facilitate analysis of a large amount of structured data and to search complex sets with simple vital terms. When this system remained great in terms of relations, NoSQL had broken the mold when it came to advanced key-value searches.

Now let’s compare the differences between these two:

Database schema
SQL: There are predefined structures and data types. The disadvantage of this approach is to store the details about new information or data, and the entire database has to be altered.

NoSQL: This is dynamic, and there are no standard schema definitions. So, unlike SQL, it can add information on the fly, and even different data sets can be stored together.

Database model
SQL: Primarily table-based DB, where individual tables with separate data types get stored in separate tables and combined while executing complex queries.

NoSQL: These are document-based, which stores as a key-value pair collection, graph databases, and documents, as well as wide-column data stores. The primary thing to note is that NoSQL DBs don't have standard schema definitions.

Scalability
SQL: The DBs are vertically scalable by adding more hardware, where a single server can be made powerful when needed.

NoSQL: Horizontal scalability by increasing the number of DB servers. The database gets spread automatically across the server cluster.

NoSQL in the Big Data world
With the latest advent of many NoSQL database platforms, it became possible for the business administrators and IT managers to get involved in database technology-related decisions making. As the NoSQL databases can aid in dynamic schema design by offering a greater potential with enhanced flexibility, the scope of scalability and customization had increased compared to the relational software. Altogether, it makes NoSQL DBs ideal for the CMS systems, web apps, mobile apps, and other industry-specific applications. With the need to involve huge volumes of unstructured data with varying field formats to handle, NoSQL shines in the Big Data scenario.

NoSQL also covers the cloud of various databases with diversified storage models. Some of the popular types of storage models are Key-Value pairs, Columnar, Graph, and Document type databases. Sometimes, this may be too much for some enterprise to take, where the use of conventional SQL technology may be needed.

Even though NoSQL represents new generation data stores, not all of its features can be identified as a radical departure from SQL. Based on the problems which the enterprises are trying to address, the decision-makers can compare the benefits and drawbacks of NoSQL over RDBMS to decide which solution suits them the best.

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