The Big Trends in Modern Data
Digital transformation is radically affecting how business systems work. Big trends in modern data are apparent in the areas of social, mobile, analytics, and cloud (SMAC). Scaling databases either vertically, horizontally, or a combination of both is what DBAs must do to propel their organizations forward and match right up with the trend of digital transformation.
The digital transformation effect of mobile
People depend on their smartphones and tablets to connect them to friends, relatives, and businesses. Through applications, they access and connect with their favorite vendors on their own time. Day or night, wherever they live anywhere around the world, mobile computing is a mainstay product of the digital transformation. The expansion of what end users can do with mobile is trending greatly.
People use mobile to conduct health monitoring, banking, find shopper deals, and more. The ease of use has become the norm and the standards are high. They want and expect fast, dependable browsing, and easy access to their accounts whenever it’s convenient for them. Database developers and DBAs must adapt to the needs of the consumer.
The digital transformation effect of cloud computing
The term cloud computing is the process of delivering services using a remote network of servers. Software-as-a-service (SaaS), Platform-as-a-service (PaaS), and Infrastructure-as-a-service (IaaS) are three notable services vendors offer to businesses. Those services make it easier for businesses to deploy, modify, store, and process applications regardless of a their size.
Cloud computing services help employers effectively run their businesses without the expense of having to heavily invest in computer equipment. Since cloud services are internet-based, the data is stored, processed and managed more simply. Hosted databases and applications must be able to withstand varying workloads.
The digital transformation effect of analytics
All that big data is huge since it comes from cloud computing, social, and mobile sources. Performing analytics makes the data useful to businesses, enabling them to compete with others in their industry. The cloud makes analytical data accessible around the clock.
Digital transformation requires database scaling
The result of trends in digital transformation calls for businesses to change their databases to adapt to flexible workloads. Horizontal scaling and vertical scaling are the two ways organizations scale their databases. Let’s explore.
Vertical scaling is the addition of resources to a current server. Investing in a CPU that’s more efficient or increasing a system’s memory are common examples of vertical scaling or “scaling up” as it is often referred. To scale down, system resources like those examples just given for scaling up are taken away.
Advantages and disadvantages of vertical scaling
Performance gets a boost in vertical scaling; however, it’s at the cost of reconfiguring the system and much downtime. There are only so many resources that a system or software can handle, so there’s a limit.
It’s true that RDBMSs, the traditional single-server kind, uses vertical scaling. But even RDBMSs have thresholds. In the case of a system with a maximum memory of 256 GB, a larger box is needed.
Vertical scaling is expensive and challenging with no guarantees that things will go as planned. Expect a considerable amount of downtime upgrading software, hardware, and the database as well.
Horizontal scaling (aka scaling out) is the addition of system hardware such as new servers. To “scale in” is to take away hardware.
Advantages and disadvantages of horizontal scaling
Horizontal scaling is an affordable way to replace mainframe computer tasks. Commodity systems can do those jobs that once were only able to be performed by larger systems.
Software plays a part in the success of any horizontal scaling project. It’s limited in its proficiency to utilize the resources of the computer effectively. Furthermore, technology restrictions of the software might become an issue.
Horizontal scaling is also limited to several machines instead of say, 100. when scaling typical database servers.
A mixed scaling effort can work well too. When vertical scaling, add resources, and in horizontal scaling, add servers.
Each solution will require a compromise; there is no perfect answer. For example, extra networking computers require more intricate managing. There’s a bit more lag when mismanagement of the software or DBMS.
Because it’s common for the costs to improve existing systems to be lower than to rearrange new systems, conducting vertical scaling can be advantageous. The drawback though is that if you make many unnecessary changes, the costs you originally saved is already spent. There is another way to reduce scaling costs and that is through cloud computing (virtualization).
SMAC is the proud recipient of digital transformation. Social, mobile, analytics, and cloud industries each have changed how we interact with others personally and professionally on a local, national, and global scale. DBAs have horizontal scaling and vertical scaling to handle big trends modern data in SMAC industries. Organizations must do what they can to handle the data upsurge to stay competitive.
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