GraalVM vs. PrestoDB (or Presto)

Its well fit for the environment where applications are written in programming languages supported by GraalVM. It's [a] very powerful and reliable, high-performer Java Virtual Machine that provides the Java Development kit i.e JDK that has the ability to compile the Java apps ahead of time. Maintenance of this tool is simple and it [increases] the efficiency of the product since it requires few resources.

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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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• Best performance of applications
• High efficiency of applications
• Reduced hardware requirements
• Lesser consumption of resources
• Universal support to multiple programming languages
• Reduced size of applications
• Creation of virtual images for testing on Android and iOS mobile operating systems
• Creation of native images
• Excellent support
• Documentations are detailed enough to learn and use easily
• Easy to use

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• 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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• It should be possible to use GraalVM EE to distribute native images of JavaFX applications for mobile platforms, especially for Apple platforms.
• Native Images are a game changer. However, compiling complex applications can be a pain. Better support for an improved transition process are a must.

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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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Like all Oracle tools, you can find a lot of documentation and also write down your questions in a forum. Sadly I don't see too many users so far but I hope it'll keep increasing and in a short period we will have more information and ofc issues fixed. So far, everything I needed I could find easily.

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GraalVM is at the top when it comes to executing Java applications in terms of speed. With its amazing fast ahead of its time compiler it helps in reducing the startup time of the applications. Also, the overall performance of the product is increased and reduces the latency as well. It supports multiple languages such as Groovy, Ruby, Javascript, R, Python, Scala, Java, Clojure, and many more.

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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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• Financial: Increased Java container count on the same hardware.
• Performance: Decreased cold start time for container startup.
• Training: Adopting GraalVM has a learning curve. This requires investment in time and resources. The benefits come through re-evaluating our current deployments for optimization.

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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