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 Actian matrix is not good for small data sets. If you have a limited data pool, or do not plan on having multiple users/clients accessing a data source, stick with a more traditional relational database model - Access for the truly small user base, or a DB2 or Oracle back end if your going to have multiple users, and moderate sized data. Actian is for LARGE data sets (Big Data, in the industry parlance). Millions of rows of data from multiple sources with various down stream systems accessing the database. It is for data analytics of large data groups and intense data mining.
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 Super fast. Aggregate query such as SUM(), Count() returns result within seconds from a table with more than billion records. Excellent data compression. Easy maintenance. We managed this database without having a full time DBA. Support ANSI SQL and ODBC/JDBC. It's easy to connect to this database from other systems. 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 Some of the bugs were annoying and QA definitely needs improvement Connectivity to Informatica and ETL providers Workload management could be better like when you compare with Teradata 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 I wish to give higher rating for the speed and efficiency in handling the queries, but only 6 because of consistent bugs we encounter
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 Faster initial response Trained professionals Very helpful in resolving issues Read full review Implementation Rating Leader failover setup is the toughest and lack of proper documentation is making things tough.
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 Actian Matrix is our first big data analytics storage platform, and as I was not involved in the POC process to compare it to other products out on the market, unfortunately I cannot say if it is better than other Big Data storage options. I can say that it out performs products such as Oracle or UDB in regards to the volume of data it can easily index and handle.
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 ROI is great, less spending on full time DBA and that money could be use to add additional node. Negative - Not many developers are well aware of this tool, it takes some time to learn. Read full review ScreenShots