PrestoDB (or Presto) vs. SharePlex

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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SharePlex really shines when set alongside GoldenGate. The licensing costs of the two products would appear to place them in entirely different ballparks yet they perform nearly identically in practice. SharePlex is suitable for heterogenous replication of one database to another. The list of targets is ever increasing, with support for all major RDBMS vendors as well as support for popular NoSQL and JSON replication. SharePlex is effective when replicating from on-premise to cloud. Whether that's migrating data, creating a high-availability presence in a public or private cloud, or populating a data mart, it does the job quite well.

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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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• SharePlex is highly configurable and versatile. It can handle virtually any kind of data replication needs.
• SharePlex is very robust. Its message queuing mechanism provides fast data transfer from the source to the target.
• SharePlex software is very stable and mature, and it is highly scalable and reliable.
• SharePlex support is exceptionally good. We are very satisfied with its support engineers.

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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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• When first introduced the Change Data Capture process was awkward. Each subsequent release has improved the process.
• Sometimes the Shareplex monitoring service in Foglight gets overly aggressive in sending out error notifications and can end up spamming the admins with email alerts for one problem. We have had to tone that down.

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We depend on it to supply data to our various OLTP and Data Warehouse environments

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It is very usable once you get over the initial setup.

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Support is very responsive. They take ownership of the problems and see them through to the finish. When a bug is found they work towards developing testing and making the fix available to us to solve the problem.

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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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SharePlex support is an award-winning team, which is available for 24 hours, and any time they have solutions with perfect expertise. Besides, SharePlex has supported data migration, with multiple reporting features that ensure there are comprehensive database evaluations. The simplicity of SharePlex installation also gives it a higher mark, is very efficient, and allows companies to understand it easily.

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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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• Postive: easy to replicate data for non-prod use
• Negative: we spent a lot time due to data out of sync

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