Likelihood to Recommend Sqoop is great for sending data between a JDBC compliant database and a
Hadoop environment. Sqoop is built for those who need a few simple CLI options to import a selection of database tables into
Hadoop , do large dataset analysis that could not commonly be done with that database system due to resource constraints, then export the results back into that database (or another). Sqoop falls short when there needs to be some extra, customized processing between database extract, and
Hadoop loading, in which case
Apache Spark 's JDBC utilities might be preferred
Read full review I find HDP easy to use and solves most of the problems for people looking to manage their big data. Evaluating the Hortonworks Data Platform is easy as it is free to download and install in your cluster. Single node cluster available as Sandbox is also easy for POCs.
Read full review Pros Provides generalized JDBC extensions to migrate data between most database systems Generates Java classes upon reading database records for use in other code utilizing Hadoop's client libraries Allows for both import and export features Read full review It does a good job of packaging a lot of big data components into bundles and lets you use the ones you are interested in or need. It supports an extensive list of components which lets us solve many problems. It provides the ability to manage installations and maintenance using Apache Ambari. It helps us in using management packs to install/upgrade components easily. It also helps us add, remove components, add, remove hosts, perform upgrades in a convenient manner. It also provides alerts and notifications and monitors the environment. What they excel in is packaging open source components that are relevant and are useful to solve and complement each other as well as contribute to enhancing those components. They do a great job in the community to keep on top of what would be useful to users, fixing bugs and working with other companies and individuals to make the platform better. Read full review Cons Sqoop2 development seems to have stalled. I have set it up outside of a Cloudera CDH installation, and I actually prefer it's "Sqoop Server" model better than just the CLI client version that is Sqoop1. This works especially well in a microservices environment, where there would be only one place to maintain the JDBC drivers to use for Sqoop. Read full review Since it doesn't come with propriety tools for big data management, additional integration is need (for query handling, search, etc). It was very straightforward to store clinical data without relations, such as data from sensors of a medical device. But it has limitations when needed to combine the data with other clinical data in structured format (e.g. lab results, diagnosis). Overall look and feel of front-end management tools (e.g. monitoring) are not good. It is not bad but it doesn't look professional. Read full review Implementation Rating Try not to change variable names.
Read full review Alternatives Considered Sqoop comes preinstalled on the major Hadoop vendor distributions as the recommended product to import data from relational databases. The ability to extend it with additional JDBC drivers makes it very flexible for the environment it is installed within. Spark also has a useful JDBC reader, and can manipulate data in more ways than Sqoop, and also upload to many other systems than just Hadoop . Kafka Connect JDBC is more for streaming database updates using tools such as Oracle GoldenGate or Debezium. Streamsets and Apache NiFi both provide a more "flow based programming" approach to graphically laying out connectors between various systems, including JDBC and Hadoop . Read full review We chose [Hortonworks Data Platform] because it's free and because [it] was an IBM partner, suggested as big data platform after biginsights platform.
You can install in more physical computer without high specs, then you can use it in order to learn how to deploy, configure a complete big data cluster.
We installed also in a cloud infrastructure of 5 virtual machine
Read full review Return on Investment When combined with Cloudera's HUE, it can enable non-technical users to easily import relational data into Hadoop. Being able to manipulate large datasets in Hadoop, and them load them into a type of "materialized view" in an external database system has yielded great insights into the Hadoop datalake without continuously running large batch jobs. Sqoop isn't very user-friendly for those uncomfortable with a CLI. Read full review It is difficult to have a negative impact, because the required investment is not that high. The big open community behind Hortonworks and related Apache Project makes it easy to put 'the wheel to meet the road' quite quickly. We have seen management meetings where the attendants were impressed by the results achieved with the datalake built on HDP. Read full review ScreenShots