Hortonworks Data Platform vs. HPE Data Fabric

I recommend [Hortonworks Data Platform] as Big Data platform in order to start your developments. It's free. It's easy to use. You can install in more server or use a sandbox with you favorite virtualization platform ( vmware or oracle virtualbox). There is also a containerized version.

Manage our data in hdfs is simple; you can interact with server with REST API.

Incentivized

If you need Hadoop and just need raw speed for I/O and have a Hadoop savvy group of engineers who don't need/like web UIs, then MapR is a great fit for you. If you are new to Hadoop or have DevOps folks that are not Hadoop gurus, choosing MapR as your Hadoop vendor will have a steeper learning curve as you will need to do more training and build more admin consoles for them.

Incentivized

• It is a well suited data platform to support big data storage and analysis, with computational efficiency, good performance, and stability.
• It is free to use. Online development community is well supported. Hortonworks engineers seem to have good experience and skill sets.
• It is easy and fast to integrate with other tools or components for big data handling and analysis.

Incentivized

• MapR allows easy integration with HBase and MapR DB.
• Easy trial server setup for product testing.
• Excellent training program to help new users get up-to-date with MapR and related products.

Incentivized

• As an open source project collection, it relies strongly on community activity. You still have the option to contract premium consulting or training services.
• Altough it is quickly evolving into Data Science tools availability (eg. Tensorflow incorporate in HDP 3), it can be cumbersome from a developer transitioning from a traditional IDE, into the notebook vs. datalake metaphore.
• As expected for a big data infranstructure, the resource requirements base line is rather high. This means that if used on premise, you need to think of about 10 machines for a minimal reasonable deploy.

Incentivized

• I think MapR's main problem is name recognition. Hortonworks and Cloudera both are big names in the industry, but their deployment mechanisms are a little more difficult to use, especially when trying to fully automate it's deployment.
• Documentation could always be better. But really, if that's your main weakness, it's everybody's weakness.

Incentivized

Try not to change variable names.

Incentivized

While Apache Hadoop is completely open sourced, Hortonworks Data Platform offers support as well as keeps pace with the open source versions. Also, the HDP open sources its own products, thus giving back to the community. I find using the Hortonworks Data Platform more intuitive than Cloudera or MapR versions.

Incentivized

Hortonworks and Cloudera are both sort of hacky. We have to do a lot of extra steps to automate those two. MapR has far fewer issues and doesn't force you into a once size fits all deployment scenario. There are multiple ways to deploy and some are more amenable to automation, MapR just has that in spades

Incentivized

• It provides a convenient way of quickly setting up a big data environment, easily setting up clusters with different configurations. It provides several security architectures that can be used as well. Since it provides a big list of components and packaged together, it is a great tool for companies to get set and utilize it for their use cases.
• Since it uses Ambari extensively to install, upgrade and manage software, it is very convenient and easy to support and operationalize the components. Alerting and notifications, ability to create custom alerts give you the capability to add any number of alerts to meet your custom needs. It provides a great way to maintain other software by creating mpacks and the ability to add custom code, and you can add other software to be managed in a centralized tool.
• The use and support of popular and useful open source software and the company's contribution to the community makes HDP a very useful tool that enables a quick, secure, easily maintainable suite of components that can help companies meet the needs of the business. What is great is that new components keep getting added based on any new useful tool that comes available, like Druid, and made available as part of the suite of components. That helps businesses keep up with new capabilities as they become available, and use them to solve their problems.

Incentivized

• Less manual intervention for maintaining a cluster.

Incentivized