The increasing use of cloud applications is leading Internet data traffic to skyrocket. According to the renowned Forrester consulting firm, the public cloud computing market will exceed 230 billion dollars in 2019. This figure is much higher than the 100 billion dollars registered in 2016. According to Cisco, by 2022 IP traffic will reach 396 Exabytes (EB) per month.

The increase in the amount of data and today’s higher information diversity demand flexible systems that allow databases to scale up based on corporate needs.

Databases are essential in the applications used by companies. They are increasingly used in a greater number of programs and tools, and organizations cannot let them get overwhelmed. It is for this reason that database scalability and server scalability are some of the most important challenges for developers.

Database Scalability: what is it?

Database scalability is the ability of a database to improve its availability and behaviour when the business demands more resources.

This scalability can have two approaches: Vertical and Horizontal.

Vertical Scaling

This approach implies adding more physical and virtual resources to the underlying server where the database is stored – adding more computing power (CPU), more memory or more storage capacity. This is the traditional approach, which consists of using a larger server to support all the data.

Horizontal Scaling

This approach consists of adding more instances or nodes to the database in order to try to deal with a higher workload. This means that when an organization needs a higher capacity, it simply adds more servers to the cluster. In addition, this cluster is usually composed of smaller, cheaper servers.

The problem with this approach is that most products do not scale this way, and depending on how they are implemented, applications will need to be reprogrammed to be able to work with the database – a true challenge for system developers.

Related reading: 10 reasons why you should include a data acquisition system in your company

3 reasons why data scalability has become a true challenge to system developers

In vertical scaling, database growth is constrained by the hardware

Even though it may seem that vertical scaling is a good option because it does not imply reprogramming the product, in reality, it has its limitations. There is a time when the hardware cannot grow anymore because the resources are limited by the maximum available capabilities at the moment that the need to scale up the database emerges.

For this reason, the best option system developers have to scale up the database is combining the vertical and horizontal scaling model.

Horizontal scaling is not supported by all applications

As we have seen in the previous section, horizontal scaling has many challenges, since there are certain products that do not support it and require reprogramming. In order to overcome this challenge, developers can go one of two ways:

  • Data replication. For read-intensive workloads, companies can have a primary copy that accepts data modifications and multiple read-only copies of that data. The disadvantage of this is that the primary copy becomes a bottleneck when writing data.
  • Federated database. This implies distributing read and write operations across many nodes. This is accomplished by fragmenting data into several database servers. There is a database replication component where certain data is stored in all or several nodes.

Scaling a relational database is hard

These databases were developed back when the volume of data was low. But nowadays, Big Data is making scaling a relational database difficult.

When scaling up a database, one can usually opt for vertical or for horizontal scaling. However, in some cases, this is not the best solution. In order to overcome these problems and perform successful scaling, the solution is NoSQL databases.

These databases are not expressly limited by a single-server architecture. These types of databases can massively scale on distributed systems. They can work with multiple servers working together, each sharing part of the load.

Using this approach, the database can operate with hundreds of servers and a vast amount of information. Furthermore, it can process tens of thousands of transactions per second with low-cost hardware operating on any kind of environment. In addition, if a node fails, other nodes can take over, thereby overcoming single point failure.

Database scalability, an opportunity for companies

Database scalability and server scalability are two key aspects when facing the exponential growth of data registered during the last few years.

In order to achieve the scalability demanded by companies in current times, developers have two choices – vertical and horizontal database scalability. But the former, in addition to being more costly, is limited by hardware. Conversely, the latter implies a higher effort by developers, but is the best option when scaling databases for all kinds of products.

Developers need to face the challenges presented by database scaling so as to increase server performance, which is essential for the sustained growth of organizations in an environment that is flooded with data.

Nexus Integra is the best solution to leverage the advantages of Big Data and improve the performance of an organization.


Ebook IOT EN