Are other companies' big data systems as bad as Amex's?


Amex is the only company I've been with so I want to know from others how it's like in other companies. Hive is so slow. Yellowbrick is fast but not all cornerstone data is there and is practically useless for my team's use case. MLS crashes so often. Ask Aida support is so sloppy and they just regurgitate the same information over and over again. Is this an Amex thing or is this just how big data works everywhere?

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Same thoughts 😂😂😂😂
Other companies use cloud platforms and latest tech stack

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That really depends on the industry, for most of the banking/finance sector, you’ll see sort of similar Architecture (Hadoop Ecosystem) as it’s not easy to migrate the complex workflows to a new technology. You’ll see most of the small/mid-sized companies adopting the latest tech stack as it is relatively easier to migrate their data. Plus the highly confidential data is another blocker to migrate to cloud. However, now a days, banks have also started to move to cloud slowly, some or the other pilots projects are running everywhere.

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I believe they are using On-prem/IBM Servers for big data applications, which is really slow compared to any of the cloud service provider like Azure, AWS, GCP.
Not sure if they will move this to cloud in future.

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They will slightly migrating the code on cloud. As per my knowledge AWS cloud will be used for big data.

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It's gcp actually. pOC completed

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Hive is always slow, Amex is my 3rd company and based on my experience,
Healthcare’s data and finance data are huge… and the tables are literally slow
The jobs take hours to run

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MLS has a new makeover!
You are supposed to use Atomos which is much much faster

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It's just a cosmetic makeover. Backend is still the gold server except for some specific usecases which uses AWS

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