Canonical OpenStack vs. PrestoDB (or Presto)

Ubuntu OpenStack is well suited for startups where there are very tight financial constraints. As Ubuntu OpenStack is open source, the startup organizations will not have to spend a lot when compared to their commercial offerings in the market. Ubuntu OpenStack is less appropriate in organizations where they don't want to have private on-prem clouds. As deploying a private on-prem cloud is a very cumbersome and tedious task, the organizations must have a dedicated team to manage such on-prem deployments.

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Presto is for interactive simple queries, where Hive is for reliable processing. If you have a fact-dim join, presto is great..however for fact-fact joins presto is not the solution.. Presto is a great replacement for proprietary technology like Vertica

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• Very easy to use, learning curve is very short. Don't need to invest months of training before using it
• Well suited with Jenkins for automated tests
• Works well on large sets of heterogeneous hardware

• Linking, embedding links and adding images is easy enough.
• Once you have become familiar with the interface, Presto becomes very quick & easy to use (but, you have to practice & repeat to know what you are doing - it is not as intuitive as one would hope).
• Organizing & design is fairly simple with click & drag parameters.

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• More customizable options while choosing virtual machine configurations would be great.
• To have regular online learning sessions directly from Ubuntu OpenStack experts [to] help users and for those who implement it.
• Giving admin more control on what privileges they can grant to their users.

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• Presto was not designed for large fact fact joins. This is by design as presto does not leverage disk and used memory for processing which in turn makes it fast.. However, this is a tradeoff..in an ideal world, people would like to use one system for all their use cases, and presto should get exhaustive by solving this problem.
• Resource allocation is not similar to YARN and presto has a priority queue based query resource allocation..so a query that takes long takes longer...this might be alleviated by giving some more control back to the user to define priority/override.
• UDF Support is not available in presto. You will have to write your own functions..while this is good for performance, it comes at a huge overhead of building exclusively for presto and not being interoperable with other systems like Hive, SparkSQL etc.

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Everybody knows VMWare which is the world's number one in data center infrastructure management. OpenStack is lot lot less expensive but doesn't offer all the functionalities you have with VMWare especially for High Availability and load balancing. You should go for OpenStack if you need an easy to use solution without the need for external consultants. If you don't have the capacity to manage your own infrastructure you had better go for VMWare.

Presto is good for a templated design appeal. You cannot be too creative via this interface - but, the layout and options make the finalized visual product appealing to customers. The other design products I use are for different purposes and not really comparable to Presto.

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• Lighter on initial spending for the organization.
• Deployments which have no vendor locking makes management decisions easier.
• Support from great community saved lot of time for engineers managing it.

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• Presto has helped scale Uber's interactive data needs. We have migrated a lot out of proprietary tech like Vertica.
• Presto has helped build data driven applications on its stack than maintain a separate online/offline stack.
• Presto has helped us build data exploration tools by leveraging it's power of interactive and is immensely valuable for data scientists.

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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