Azure SQL Managed Instance is a scalable cloud database service that combines SQL Server database engine compatibility with a fully managed and evergreen platform as a service.
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IBM Cloud Functions
Score 8.0 out of 10
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IBM Cloud Functions is a PaaS platform based on Apache OpenWhisk. With it, developers write code (“actions”) that respond to external events. Actions are hosted, executed, and scaled on demand based on the number of events coming in. No servers or infrastructure to provision and manage.
Azure to our enviironment where we have everything integrated stacks up far better than MySQL where we would have to reinvent and use everything to fit a MySQL environment including the data and the commands within that data. Furthermore, doesn't work really well on SQL …
AWS Lambda is 100 times more robust than IBM cloud functions. They essentially do the same thing, but AWS works. AWS is stable. we have had epic failures with cloud functions. Support was horrible. We literally had an open ticket with them for 2 months and it literally went …
AWS Lambda might be more suited for larger scaled companies looking to consistently access similar features at a higher volume/frequency, but for smaller teams with a limited budget, IBM's Cloud Functions are a competitive choice
Runs the supply chain workload well. Able to provide proper alerts when the cpu is not enough to run the workload. Is able to run the update stats automatically as the data changes. Scales very well for most oltp apps. Has good dashboards to show what is going on the database.
IBM Cloud Functions [is] not the worse product on the IBM cloud. I decided to write this review as I thought it would be balanced. I would still use functions to set up a serverless architecture where execution time is pretty quick and the code is relatively simple. I wouldn't use IBM Cloud Functions for async calls obviously, as costs could be higher. The functions documentation is lacking in terms of CI/CD, and there are unexplainable errors occurring - like the network connection that I mentioned. So I wouldn't just rely on IBM Cloud Functions too much for the entire system, but make sure it's diversified.
Validate raw data files - check the validity of raw data input to the system, to make sure we analyze only the relevant data. The raw data stream rate is hard to be predicted, since it depends on real world activities.
Analyze raw data - analyzing of valid raw data, described above.
it runs the workload very well without causing any issues to the business. there are many applications running on Azure SQL Managed Instances in my organization. Most users are happy with its performance. Is able to provide good dashboard for the visibility of the workload. Can add cpu without a downtime to deal with high workload.
Azure to our enviironment where we have everything integrated stacks up far better than MySQL where we would have to reinvent and use everything to fit a MySQL environment including the data and the commands within that data. Furthermore, doesn't work really well on SQL Management Studio which makes it completely useless for what we are trying to do.
AWS Lambda is 100 times more robust than IBM cloud functions. They essentially do the same thing, but AWS works. AWS is stable. we have had epic failures with cloud functions. Support was horrible. We literally had an open ticket with them for 2 months and it literally went nowhere. They said it could do 100 calls a minute. We proved over and over that we couldn't get above 20 without getting failures. They had NO explanation whatsoever. The ticket got closed because we were tired of asking them questions and getting no understandable or usable response.