How to Effectively Manage Big Data and Cold storage?

Cold and Hot are the common terminologies used in Big data storage. The levels have been categorized based on the frequency of the data that is been accessed. Historically hot data was close to the heat of the spinning drives and the CPU’s, and the cold data was on tape or a drive far away. There are no standard industry definitions of what hot and cold mean when applied to data storage, so you’ll find them used in different ways, which makes comparing services challenging. Generally, though, hot data requires the fastest and most expensive storage because it’s accessed more frequently, and cold (or cooler) data that is accessed less frequently can be stored on slower, and consequently, less expensive media. 

Data retrieval and response time for cold cloud storage systems are typically much slower than services designed for active data manipulation. Practical examples of cold cloud storage include services like Amazon Glacier and Google Cold line. Storage prices for cold cloud storage systems are typically lower than warm or hot storage, but cold storage often incur higher per-operation costs than other kinds of cloud storage. Access to the data typically requires patience and planning.
Cold storage also can be used to describe purely offline storage — that is, data that’s not stored in the cloud at all, so sometimes when you hear about cold storage it is the old definition of cold storage: data that is archived on some sort of durable medium and stored in a secure offsite facility without a connection to a network.

How is it stored?

1.Use inexpensive but dependable cold storage
For big data that is seldom used or archived, slow hard drives and tapes are the most commonly used storage media. The key is to test your disks and tapes periodically to ensure they are in good working order. Also, avoid the temptation of just relegating your older drives and tapes to archiving and data backup functions--these resources still have lifespans and are more likely to fail if they are older assets.

2.Consider cloud-based cold storage
If you don't want to store your big data onsite or in a physical off-premises facility, going to the cloud is an option. There are a number of cold storage cloud choices, and you might find an option that is the most economical alternative to storing all of your cold data.

3.Perform annual evaluations of cold storage data
Just because you have a means of storing unused data doesn't mean that you should routinely be storing all of it. If you haven't already, now is the time to sit down with end user management and your legal department to determine which data you should keep and which you can discard. You should evaluate your cold storage data every year.

4.Use data/storage automation
Most storage providers provide tiered data storage that is facilitated by artificial intelligence (AI). This AI takes the rules for storing data that you define and automatically applies them to determine where data is stored. 

Most big data storage management strategies focus on making data readily available to users in real time, but this also increases budgetary spend for storage and processing. Companies can help offset these larger expenditures by looking at the seldom used big data that they have under management so they can ensure that this data is being stored at least cost. For this data, cold storage media is a secure, reliable, and affordable solution. 

By haripriya.krishnakum Krishnakumar | 03 Dec 2019 | 0 Comments