Likelihood to Recommend
MonetDB is great when you are performing adhoc queries on a large set of data. For example, if you store data in a typical RDBMS such as MySQL or Postgres and want to join large tables for analytics but the query runs unacceptably slow then MonetDB can act as a second database to offload complex queries. Based on my experience, it may not be a production-ready database since there aren't many DBAs familiar with it and due to lack of documentation, maintenance can become a little tricky.
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Presto is for interactive simple queries, where
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 It is easy to use. You are able to input lots of data and it understands and populates information. Able to change settings on the fly to use with your needs. 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 This is an open source software so there are obvious drawbacks, the biggest of which is a lack of documentation. MonetDB does not seem to be well known outside of the academic environment so there is less information when you are searching for answers of any type. I'd like to see more use cases and/or best practices so that commercial companies like ours can optimally use all of its highly performant features. The code is written in C/C++ and this can be negative if you are a mainly java-shop and need UDF - User Defined Function. 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 Alternatives Considered
We have used Five9 in my previous company but on a much smaller scale. It was more expensive, however we were using it for a max of 50 employees, now we need a much bigger platform. We also used Five9 for other things, like phone dialers etc. so it was a little different.
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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.
Read full review Return on Investment If you are familiar with a general database concept and played with open source products before then MonetDB will give you immediate return in terms of productivity since developers can quickly develop and verify their test cases involving back-end database with a large sample data set. There is a stiff learning curve due to lack of documentation and sparse information available on the internet. Overall experience has been positive since MonetDB gives you another option when it comes to building out a data warehouse. 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