Likelihood to Recommend Well suited: A tiny-mid sized company with no immediate plans of growing the volume of their data processing, that can afford long response times from support. Also it helps if you are not prone to put your hands on Linux and Spark configuration. In fact, it can make things go really faster if you also work with the bundle-in Jupyter. And, if you need to perform some diagnostics and / or administrative tasks, that's full of tools to find an understand the Root Cause. Ideal for non experts. Less appropriate: Big Data company, intense on demand cluster creation, mission critical, costs reduction, latest versions of libraries required, sophisticate customizations required.
Read full review 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 Read full review Pros Data is presented without interfering others (IT or other dept). Data is managed properly and is available for retrievable any time. Legacy use of CD/DVD and Pendrive are not required. Read full review 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. Read full review Cons The only problem I have come across is when loading large volumes of data I sometimes get an error message, I assume this means something is corrupt from within. I would love a way for this to be resolved without having to start over. Read full review 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. Read full review Usability Azure HDInsight is usable on the top of Azure Data Lake and gives us the benefit of analyzing large scale data workload in Hadoop. Usability and support from Microsoft are outstanding.
Read full review Support Rating Inexpert, isolated teams... not good for support an excessively complex platform. Lots of weeks or months for a complex problem troubleshoot. Many time lost stuck on MindTree, before the case was finally escalated with Microsoft!
Read full review Alternatives Considered At this time I have not used any other similar products... I am open to it but Azure HDInsight and its components really work well for our organization.
Read full review 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.
Read full review Return on Investment ROI is of course there, as no legacy software for data presentation. No manual intervention for data retrieval. Data is available anywhere as requested. Read full review 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. Read full review ScreenShots