Cooking with Data: A culinary journey through storage technologies

By | 7. August 2018

As a consultant, I find it sometimes really hard to explain to customers what is the difference between SSD/SAS/SATA/cloud etc. And what this means in particular for their data.

I´ll try my best to explain this in this blog. The people who expect a high level technical contribution here, I’m afraid I have to disappoint straight away. Some comparisons you’ll see might not be perfectly fitting, or you, the techie readers, might interpret those differently. Nevertheless, I still dare you to read further.

“Working with data or processing it has a lot in common with cooking. ” You don’t think so? See for yourself!
Cooking ingredients in the pan need to be processed in order to be consumed later. Just like a CPU. The data (our main ingredient) already in the CPU is processed as well.

The ingredients that I need for my recipe, I have already put aside on my cutting board. Similarly the data is kept in the RAM, “next to” the CPU, so it can be processed immediately.

Products that I don’t immediately need for my meal, i.e. for direct processing, I keep in the refrigerator. I can quickly go from my cooking station to the fridge and get the next ingredients from there. Everything I need for preparing my meal is stored in the fridge. It’s convenient and fast. Just like a SSD memory. I have an access to the data stored very quickly.

And now dear reader, the cooking drama begins. Those of you who are experienced in kitchen already know what I’m talking about. Suddenly you realise there’s an ingredient in the recipe that you currently don’t have in the fridge. Let’s just say it’s peas. You look into the pantry cabinet if you have another can of peas… These are SAS drives nowadays.No peas in stock? Oh no! You run quickly down to the basement (if you happen to have one) and check if there’s still some peas left in the freezer. This takes some time of course. Getting down to the basement, looking for peas, getting back upstairs quickly… In the meantime, I’ve put the temperature down on the burner. So the processing speed is reduced. I’m not able to put in my pan (CPU) fast enough the peas (or data) in order to continue the cooking process. My guests are starting to get hungry. In this case it’s like when your users waiting for the data on a SATA disk 😉
Unfortunately, I couldn’t find any peas in the freezer. I don’t frequently use peas in my recipes, so I don’t have any left neither in the fridge nor in the freezer. But I know where I can find peas for sure… In the supermarket! This is the place, where I could find all the ingredients I  would ever need for cooking. In this case, for me the supermarket is like “the cloud”! I get myself in the car, drive to the supermarket, buy peas, go back and can resume with the cooking.

This is a very nice dilemma with the cooking. Unfortunately, we can’t all buy massive fridges for the kitchen to have all possible ingredients at hand at any time.

Luckily enough, we are able to handle data differently in this day and age. So we can get all-flash systems that hold all the ingredients/data for us.

I don’t necessarily need to have a whole can of peas in the fridge all the time. It takes too much space. Instead, I just keep some pea pods in the fridge. If I happen to need 300 pea pods, the storage system would simply say “Look, there seems to be a pea, just take it 300 times.” This is in my opinion what deduplication is.

 

Or for instance I happen to have a medium size refrigerator. It contains all the ingredients, I need regularly for cooking. The ingredients that I rarely need or occasionally for a special recipe, my fridge can then simply order them from the supermarket. Hey, this is actually possible in the reality of data. The process can be compared to transferring my data with NetApp Fabric Pool. More about Fabric Pool, you can read in my previous post.

I hope you enjoyed my culinary journey through the storage systems and you could take something for yourself personally from this post. For questions or comments just use the comment function in the blog.

Greetings from

Der Schmitz

Disclaimer: This post represents my personal observations and is not officially authorized by NetApp or others. misinterpretations or misunderstandings reserved.

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