Working with Big Data means being able to meet strict requirements in terms of computing capacity, storage space and security. Backup options for Big Data are diverse, ranging from the most elaborate and complex on-premise solutions to the convenience of Cloud backup solutions.
Companies that work with Big Data know very well the requirements necessary to collect, store, process and take advantage of this particular type of data. The six uses of Big Data (Volume, Variety, Speed, Veracity, Value and Variability) define the complexity of this data model that, above all, needs an extra technological effort in order to extract value from those data for the benefit of the business.
The loss of data is inadmissible in any professional environment and, when it comes to Big Data, not only have to worry about keeping the data safe and implementing a good backup system that allows us to recover from a disaster. In addition, we have to have sufficient capacity and processing power to support the workloads required by Big Data or when the big data is cracked or broken so it can be easily fixed by flash drive repair service.
There are several storage solutions prepared to meet the Big Data storage requirements. We can talk about local solutions, cloud-based solutions and a combination of both that make up hybrid storage solutions.
Each project and each organization will have its own needs and requirements in terms of data. Therefore, giving a single solution is impossible because it would not work for all scenarios. So it is necessary to explore the different existing alternatives and, from the particular perspective of each project, to choose that option that gives us the greatest advantages.
Different needs, different solutions
The storage and backup of Big Data is a problem for many companies, who need to find a solution that maximizes security and allows the recovery of data at the appropriate speed and with the required reliability.
When opting for local data storage, the options and alternatives are multiple. With local data storage, companies can use file-level storage solutions with a NAS schema, for example, large-scale storage or hyper-converged storage.
These solutions have their advantages and disadvantages. In terms of pure features and the incremental capacity that can be achieved, they are good solutions. The problem is that the cost of these solutions exceeds, by far, the economic capacity of small and medium enterprises that work with Big Data. They are expensive solutions.
The best thing is to make use of Cloud-based backup services in combination with backup infrastructure, whenever that is possible. By distributing backup data between the local infrastructure and the Cloud, companies can efficiently leverage their storage space and make the entire backup process cost-effective.
Cost is one of the important arguments when we talk about integral solutions in the Cloud. If we opt for a storage and backup solution in the Cloud, the dedicated budget will be significantly reduced compared to on-premise solutions. In addition to this, any additional aspect such as the processing speed, measured in IOPS (Input / Output Operations Per Second or input/output operations per second), data security or storage capacity, will be covered by the increasingly complete Cloud solutions. As always, we must resort to the right provider to our needs and with enough experience to offer a seamless service.
By opting for the Cloud, companies can scale virtually without limits as their needs increase. Every time you need to expand resources, the cost is proportionally reduced compared to any solution on-premise, which achieves the goal of storing and supporting Big Data without the need to make large investments in infrastructure, personnel and maintenance
The storage of Big Data requires storage capacity and processing. In the first case, in terms of storage capacity, the Cloud has proven capable of meeting the most demanding expectations. On the other hand, the computing needs in terms of Big Data can also be satisfied with the Cloud. The recommendation is that the data analysis is done in the Cloud to, on the one hand, have the necessary resources in each situation, on demand, and, on the other hand, to have a proven infrastructure, secure and with the ability to guarantee not only the availability of data, but also a good response to any eventuality or disaster.