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 QuestDB is well suited for any use case where you need to store large amount of data and the performance is the key factor - for both reads and writes. So use cases like market data storage in financial industry, any kind of telemetry, etc.
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 Extreme performance. Super easy to use. Compatibility with Influx line protocol. PostgreSQL compatibility. Out of order timestamps. Support for multiple records with same timestamp. Integration with Grafana. Team responsiveness. 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 New project so needs a bit polishing. 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 were looking for time series database that will be able to handle L2 market data and came across QuestDB. From the beginning we were impressed how well the QuestDB performs and that it actually significantly outperforms all other open source TSDB on market like
InfluxDB ,
ClickHouse ,
Timescale , etc. Apart from the excellent performance it is also super easy to use and deploy which makes the experience of using the database very pleasant - we were able to be up and running and storing data within few hours. Topic itself is the QuestDB team that is super responsive on their slack channel and always ready to help with any query. They are constantly improving the product and if there is some missing feature that is blocking you from usage they always try the best to implement such feature asap and release a new version - one of the best support I have ever seen so far in open source community.
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 Reduced cost. Increased efficiency. Faster time to market. Read full review ScreenShots