Apache Hive is database/data warehouse software that supports data querying and analysis of large datasets stored in the Hadoop distributed file system (HDFS) and other compatible systems, and is distributed under an open source license.
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Apache Derby
Score 7.0 out of 10
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Apache Derby is an embedded relational database management system, originally developed by IBM and called IBM Cloudscape.
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.
If you need a SQL-capable database-like solution that is file-based and embeddable in your existing Java Virtual Machine processes, Apache Derby is an open-source, zero cost, robust and performant option. You can use it to store structured relational data but in small files that can be deployed right alongside with your solution, such as storing a set of relational master data or configuration settings inside your binary package that is deployed/installed on servers or client machines.
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.
Apache Derby is SMALL. Compared to an enterprise scale system such as MSSQL, it's footprint is very tiny, and it works well as a local database.
The SPEED. I have found that Apache Derby is very fast, given the environment I was developing in.
Based in JAVA (I know that's an obvious thing to say), but Java allows you to write some elegant Object Oriented structures, thus allowing for fast, Agile test cases against the database.
Derby is EASY to implement and can be accessed from a console with little difficulty. Making it appropriate for everything from small embedded systems (i.e. just a bash shell and a little bit of supporting libraries) to massive workstations.
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.
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.
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
SQLite is another open-source zero-cost file-based SQL-capable database solution and is a good alternative to Apache Derby, especially for non-Java-based solutions. We chose Apache Derby as it is Java-based, and so is the solution we embedded it in. However, SQLite has a similar feature set and is widely used in the industry to serve the same purposes for native solutions such as C or C++-based products.
Being Open source, the resources spent on the purchase of the product are ZERO.
Contrary to popular belief, open source software CAN provide support, provided that the developers/contributors are willing to answer your emails.
Overall, the ROI was positive: being able to experiment with an open source technology that could perform on par with the corporate products was promising, and gave us much information about how to proceed in the future.
