AWS provides a tool to control multiple services and that tool is known as AWS Cli. As the name suggests, the user can operate this tool from command line, and it offer a lot of functionalities that the user can bind with their application code also. If the data is on AWS and struggling to be embedded with the activities of the user’s application code, UDLCC be of great assistance for you.

UDLCC Recent development with AWS Cli

In a digital world we all understand the power of data. All organizations maintain their databases for some current as well as the future requirements. When database sizes are lite it is easy to maintain both from operational and economical perspective. But, it becomes heavy on the pocket and sometimes nonoperational when the database sizes are heavy. Historical data which can be around 5 or 10 years old, are not frequently used. So, this might come to you as a shock that that you are paying for the maintenance of the dataset that you don’t even use frequently. It is true that the old data cannot be discarded since it can come to use at any given point by the client or it can be a clause in your agreement with the client that you need to keep the data with you. However, you don’t have to burn a hole in your pocket to maintain that data. There are cost-effective ways to maintain such data.

Most of the industry organization now a days are using Cloud (either AWS or Google) to maintain their data. But, what is known to many is the fact that maintaining database on Cloud costs the user a fortune. So, why would you invest so much in datasets that are not even used so infrequently. Imagine a scenario in which you are maintaining telecom data and someone demands a CDR for the year 2007. Although these requests are not very common, you still have to pay and maintain the old data just the way you are maintaining your current datasets.

How does UDLCC help?

Our aim at UDLCC is to help you save money and the time that you invest into the maintaining of this historical data.

With the help of our technique known as the ‘Glacier Offline Database, we will be able to bring down your data maintenance cost at least 30 times. Glacier is storage in AWS and it costs very less to store data. The user will be provided data on request while it takes anywhere about 5-6 hours to get even few MB of dataset. Once you have your new dataset, you will have to convert it into logical shape to get information.

In "Glacier Offline Database" technique you just have to set your storage style in AWS Glacier and pass certain parameters to get those data in few minutes. To fetching the historical data, organizations take up to 24 hours to provide them. But, when you use the Glacier Offline Database technique, you will be able to provide those datasets in only a couple of minutes. This brings down the time required as well as the cost.

It is obvious for most users to think that there can be several techniques available in the market that provide these services. But, with "Glacier Offline Database" technique, you just have to set your storage style in AWS Glacier and pass certain parameters to get those data in just few minutes.

To know more about this please write us or fill enquiry form.

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