Likelihood to Recommend Software work execution is on a large scale, it is good to use for new projects or organizational changes, data lineage mapping has always been dubious but this one has had good results. You can store and synchronize data from different departments, the storage process can be manual but it is best automated.
Read full review 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.
Read full review Pros Apache Hive allows use to write expressive solutions to complex problems thanks to its SQL-like syntax. Relatively easy to set up and start using. Very little ramp-up to start using the actual product, documentation is very thorough, there is an active community, and the code base is constantly being improved. Read full review 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 Cons Some queries, particularly complex joins, are still quite slow and can take hours Previous jobs and queries are not stored sometimes Switching to Impala can sometimes be time-consuming (i.e. the system hangs, or is slow to respond). Sometimes, directories and tables don't load properly which causes confusion Read full review 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 Likelihood to Renew Since I do not know the second data warehouse solution that integrate with HDFS as well as Hive.
Read full review Usability Hive is a very good big data analysis and ad-hoc query platform, which supports scaling also. The BI processes can be easily integrated with Hadoop via the Hive. It can deal with a much larger data set that traditional RDBMS can not. It is a "must-have" component of the big data domain.
Read full review Support Rating Apache Hive is a FOSS project and its open source. We need not definitely comment on anything about the support of open source and its developer community. But, it has got tremendous developer support, awesome documentation. I would justify the fact that much support can be gathered from the community backup.
Read full review Alternatives Considered Besides Hive, I have used
Google BigQuery , which is costly but have very high computation speed. Amazon Redshift is the another product, I used in my recent organisation. Both Redshift and BigQuery are managed solution whereas Hive needs to be managed
Read full review 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.
Read full review Return on Investment Apache hive is secured and scalable solution that helps in increasing the overall organization productivity. Apache hive can handle and process large amount of data in a sufficient time manner. It simplifies writing SQL queries, hence helping the organization as most companies use SQL for all query jobs. Read full review 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 ScreenShots