NoSQL is the New Hadoop

NoSQL is the New Hadoop

The key challenge businesses world over face today is managing data explosion. The traditional
business concepts that were used to manage data have become obsolete now. The changing
dynamics in the technological landscape has led to newer and more sophisticated tools that
work on data at jet speed these days. I’ve found that emerging technologies like the New
Hadoop framework aim at better solution for big data systems.
Why relational database is not relevant any more?
Relational database management system or RDBMS in the traditional setup have been the only
option used by organizations to manage their databases effectively. The relational database
helps to organize data in a structured manner based on relational model. Though I think
keeping data in a structure form is good for enterprises, in case of huge volumes this can
become a big burden, leading to progressive decline in performance. The scene will be more
frequent, once the data becomes too big to manage. This makes RDBMS an inappropriate
scalable solution for big data.
Generic Data Processing Framework
Since relational database could not satisfy the demands of data, an alternative solution was
required. This resulted in the introduction of data processing software. I’ve had many queries
from those new to database management about what is Hadoop? It is nothing but software
framework that enables parallel processing of huge amounts of data in a large commodity
hardware cluster. The entire processing is error free and unswerving. The software can execute
queries and also read operations on huge data sets, which have the capability of scaling to as
big as petabyte sizes. The software framework has an unrivalled price performance ratio that is
brought about by the flexible analytics feature it exhibits. Structured, semi-structured, and
unstructured data can be analyzed with the same fixed framework.
Parallelism and its Uses
The main advantage of Hadoop is its ability to route parallel queries in the form of huge
background batches within the same server farm. This reduces the expenses of using an
additional hardware as was the case in traditional database systems. And in my opinion, the
time and effort needed is greatly reduced. The concept for this type of framework originated
from search engines like Yahoo! and Google, which use massive inexpensive servers to read
parallel queries, so search indices and related data structures can be formed. But when the
data to be analyzed became alarmingly huge in size, the system could not keep up as the scaling
needed lots of coordinating and caching methods to reduce the alignment required.
New Heights in Scalability
The introduction of new Hadoop technology like YARN (Yet Another Resource Negotiator) has
brought new heights to the scalability factor of the file system. This new addition has enhanced
the distribution processing of the system with the successful management of big data. The
highlight of this new technology is clear assigning of responsibilities to different components,
thus making it a highly desirable system that I’d readily recommend.
Database for Dealing with High Data Volume
I’d suggest the emergence of new databases that are appropriate for unstructured data is vital
for data management. What is NoSQL? It is a new generation database management system
that enables easy access and utilization of poly structured data in large volumes. Some of the
key points it addresses are:
 Cost effective scalable solutions
 Flexible assessment of data structures, which do not conform to the relational system
like graphs and key- value information
The database performs a horizontal type of scaling called sharding in which each server has a
separate database that is partitioned physically, so each has the data stored in the local disks in
it. The drawback I’ve experienced here is you cannot do joins, schema changes or transactions
and you may also need to compromise the ACID (Atomicity, consistency, isolation, and
durability) which results in relaxing of the consistency factor.
Prudent Use of Databases
When compared to the relational database model, I’d suggest that the schema free file system
has more advantages. Though the relational database will still be in use, organizations will
prefer to work with applications that run on NoSQL. This is because it can bring about far
reaching success in all types of environs including content management, help in offloading the
query volume and providing a high performing data store and ad targeting areas. The similarity
between Hadoop and NoSQL databases is the scalability factor.
For users who don’t need high performance as a priority, but want the flexibility that a file
system can bring, I’d recommend a document database as a good solution. Relational database
is for those who perform more than one transaction across various data objects. Since NoSQL is
more about scalability and high performance, its drawbacks will not matter much for those who
are in exclusive need of its features. The ability to alter an application without going via a DBA,
gives it a definite advantage. You are welcome to share your thoughts on Tata BSS page.