D2iQ Mesosphere vs. Snowflake

Mesosphere is well suited for orchestrating workloads. It supports Docker as a container as well as support others. It is highly suitable for running resilient and auto recovering big data/application containers. Mesosphere has proven time and again to be production ready at a massive scale. It supports native single button/API call scale up and scale down and supports various deployment patterns like Blue-Green and others.

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Snowflake is well suited when you have to store your data and you want easy scalability and increase or decrease the storage per your requirement. You can also control the computing cost, and if your computing cost is less than or equal to 10% of your storage cost, then you don't have to pay for computing, which makes it cost-effective as well.

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• Deploying mesosphere and friends (e.g. marathon)
• Deploying applications (e.g. Cassandra, Jenkins, Spark) on to mesosphere
• Providing value add components such as velocity, and marathon-lb

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• Snowflake scales appropriately allowing you to manage expense for peak and off peak times for pulling and data retrieval and data centric processing jobs
• Snowflake offers a marketplace solution that allows you to sell and subscribe to different data sources
• Snowflake manages concurrency better in our trials than other premium competitors
• Snowflake has little to no setup and ramp up time
• Snowflake offers online training for various employee types

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• Setting up is a bit of a hassle, especially ZooKeeper state management and mesos and marathon quorum.
• Occasionally, I observed some failures when deploying something onto Marathon. Logging or detailed error reporting can help.
• Stale containers and inconsistent states resultant of the cluster failure are hard to solve and need a complete system restart to get it back to normal state.

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• Add constraints for views and not just for tables
• Do not force customers to renew for same or higher amount to avoid loosing unused credits. Already paid credits should not expire (at least within a reasonable time frame), independent of renewal deal size.

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SnowFlake is very cost effective and we also like the fact we can stop, start and spin up additional processing engines as we need to. We also like the fact that it's easy to connect our SQL IDEs to Snowflake and write our queries in the environment that we are used to

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Because the fact that you can query tons of data in a few seconds is incredible, it also gives you a lot of functions to format and transform data right in your query, which is ideal when building data models in BI tools like Power BI, it is available as a connector in the most used BI tools worldwide.

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We have had terrific experiences with Snowflake support. They have drilled into queries and given us tremendous detail and helpful answers. In one case they even figured out how a particular product was interacting with Snowflake, via its queries, and gave us detail to go back to that product's vendor because the Snowflake support team identified a fault in its operation. We got it solved without lots of back-and-forth or finger-pointing because the Snowflake team gave such detailed information.

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I happen to like mesosphere because it integrates well with a Jenkins based workflow, Deis is a little more Heroku like and it's not clear how to fit that model into a continuous-integration process. Kubernetes has also been criticized for being complicated.

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I have had the experience of using one more database management system at my previous workplace. What Snowflake provides is better user-friendly consoles, suggestions while writing a query, ease of access to connect to various BI platforms to analyze, [and a] more robust system to store a large amount of data. All these functionalities give the better edge to Snowflake.

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• I see mesosphere as having a positive impact overall on the industry trending Docker and containers in general.
• Seeing how mesosphere helps and simplifies things for the developer and ops, it is definitely a game changer.
• Native support of on demand scaling up and down as per the need is one of the best features.

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• With separate compute and storage feature, the queries get executed quickly and it improves our overall productivity.
• Earlier we were using a different product for analytical purposes, but with Snowflake's in-built analytical feature we are now able to save money.
• Snowflake is cost efficient, features like auto suspend for compute resources helped to control the costs.

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