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 I would recommend
MongoDB Atlas to every company who have a significant need in the NoSQL database and do not want to manage their infrastructure. Using
MongoDB Atlas can significantly reduce your management time and cost, which saves valuable resources for other tasks. It also suits a smaller company as
MongoDB Atlas scales up and down very quickly.
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 DB Provisioning. DB Management. Gene Baker Vice President, Chief Architect, Development Manager and Software Engineer
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 As an independent entity, MongoDB Atlas is not included in existing subscriptions from AWS or Azure, requiring an additional support plan and reliance on a third party. 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 We love
MongoDB support and have great relationship with them. When we decided to go with
MongoDB Atlas, they sent a team of 5 to our company to discuss the process of setting up a Mongo cluster and walked us through. when we have questions, we create a ticket and they will respond very quickly
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 MongoDB Atlas has been in the market for very long time and there are bunch of documentation, training and support for it. It also is specifically designed for the use case similar to our project and big companies in the market uses them for very high load which made us confident about our choice.
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 Improved our maintainability Reduced daily work compared to self-hosted solutions Reasonable pricing compared to value Read full review ScreenShots