Hevo Data vs. Mirantis Kubernetes Engine

It is of great help for unstructured data sources. The way Hevo Data flattens the high nested data is amazing. Schema management is also good by Hevo Data. The way it's tell about the data type and then we can identify any error in the model. Additionally, It is very easy to setup for any new user and once model is created then we do not have to worry about the script maintenance and updating the script daily.

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[Mirantis Cloud Native Suite (Docker Enterprise)] is the most advanced tool till now, which works as a VMs
and separates any single application from the dependencies. Also, this tool is
helping me in the agile development of the processes. It is strongly recommended to
almost all major organizations.

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• Extract
• Load
• Transform
• Support

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• Containers - Docker is the go-to when using Containers, which are super useful if you need an environment that works both for Windows and Linux
• Efficiency - Docker is very lightweight and doesn't demand too much from your CPU or server
• CI/CD - Docker is excellent for plumbing into your build pipeline. It integrates nicely, is reliable, and has an easy set up.

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• Support - their support teams try to be helpful, but often miss the mark
• Error logging - we've run into a few issues debugging errors and limited support is provided by Hevo

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• Containers are often opaque - if a container doesn't work out of the box, it's messy to fix.
• Logging is complexified by the multiple containers and logs are often not piped to places you expect them to be.
• Networking is complexified due to internal port mapping between containers, etc.

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Docker's CLI has a lot of options, and they aren't all intuitive. And there are so many tools in the space (Docker Compose, Docker Swarm, etc) that have their own configuration as well. So while there is a lot to learn, most concepts transfer easily and can be learned once and applied across everything.

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The community support for Docker is fantastic. There is almost always an answer for any issue I might encounter day-to-day, either on Stack Overflow, a helpful blog post, or the community Slack workspace. I've never come across a problem that I was unable to solve via some searching around in the community.

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1. Cost efficient 2. Creation of automated pipeline 3. Can load data from multiple data sources 4. Updates data in near real-time - We were able to get near real time insights from the data model which we have created in hevo 5. It has good integration with different BI tools

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We've used XAMPP, PHPmyAdmin and similar local environments (our app is on PHP). Because of how easy you can change the configuration of libraries on PHP and versions (which is SO painful on XAMPP or other friendly LAMP local servers) we are using Docker right now. Also, being sure that the environment is exactly the same makes things easier for developing.

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• Comprehensive results from the data processing is a perfect approach from the tool.
• Authentic data models brings a high automation process and more productivity.
• Expansive data sourcing brings clarity and genuine results after inferential analytics.

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• Docker has made it possible for us to deploy code faster, increasing the productivity of our development teams.
• Docker has made it possible for us to decentralize our build and release system. This means that teams can deploy on their own schedule and our dev ops team can concentrate on building better tools rather than deploying for the teams
• Docker has allowed us to virtualize our entire development process and made it much simpler to build out new data centers. This, in turn, is significantly increasing our ROI by providing a path forward for internationalization.

Incentivized

Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info