Hortonworks Data Platform Reviews

We use it for data science activities.

Data is now available.

I have no preferences towards any feature.

• Security
• Performance
• Workload management

Its ability to scale out seamlessly with little to no effort is very valuable to us. All the tools in the stack are built from the ground up to support massive amounts of data.

It allows us to provide our customers with data insights that they previously were unable to obtain.

There have been some governance initiatives, but they are far from production ready. I would like to see a big improvement in that space, as governance is critical in many regulated industries.

I've been using it for one year.

Stability is good if configured properly, but for some tools such as for instance HBase, configuration is extremely hard to get right.

Scalability is superb.

I never interacted with customer support.

Cloudera and vanilla Big Data tech. We continue to use them alongside HortonWorks, depending on our clients preferences and needs.

Cloudera and vanilla Big Data tech. We continue to use them alongside Hortonworks, depending on our clients preferences and needs.

With Ambari, it is pretty straightforward, but I have no idea why they prefer FQDN over IP.

My colleagues and I are the implementation team. The general advice is to start out with a small enough scope. Try to get an MVP up and running before bringing out the big guns./

Licensing is on a per node basis and it encourages people to scale vertically rather than horizontally yet the whole purpose of the tools they sell is to scale horizontally. I do like that everything is also available freely for those that do not require support.

Make sure you understand what happens under the hood. Out-of-the-box tools are sub-par. Customisation is the way to go for now.

There’s not only one, the all-stack of Hadoop is valuable, the distributed file system HDFS, Spark, Kafka, HBase, etc. Hortonworks has certainly got the most up-to-date version of each component of Hadoop.

Compared to the other Hadoop distributions, the Ambari server provides the user an easy way to manage, to administrate and to configure their cluster. Ambari also provides a single view that gives you the possibility to use different Hadoop components from the same web interface.

This product gives the possibility to the organization to easily and quickly install and configure a Hadoop cluster. With this cluster, the organization will be able to store and process their data and bring out some specificity on it. For example, unknown common points between their clients or key elements that will increase or decrease the churn of the client.

It would be interesting to have an easy way to implement multi-tenant for HDFS with federation. At the moment, you have to do it manually in command line.

Also, it needs to support having more than two HDFS namenodes. HDFS supports more than 2 namenodes, but Hortonworks doesn't.

I work with it in different projects and POCs for two years now.

The only issue that I had was when I tried to reinstall the software on every node. You have to manually clean up everything, as Hortonworks doesn’t provide the ability to perform a clean uninstall (software, library, log, configuration files, etc). In some case, it can generate some problems if the uninstall has not done correctly.

I never had to create a case at the support, so I don’t know. I always find the answers to my questions on the web (forum or blog). There’s a big community that can support you.

I also used Cloudera, MapR, and Microsoft HD Insight.

The first time, I didn’t know anything about Big Data and Hadoop, so yes it was difficult because I did not clearly understand what I was doing.

The implementation was at the clients datacenter. My advice is to perform a POC on premise or via a virtual machine to learn how to use it and how to tune the configuration of each Hadoop component.

When implementing it in production, firstly you need to have a clear view of the requirements you need to perform the install. For example, if you are using a local repository to install the software, it has to be updated with Hortonworks sources, especially if there are security rules (firewall access, root access limitation, etc.).

My last piece of advice is that if you have a heavy load, it is really important to implement the solution on premise, not in a virtualized environment. If you do both, you will see the difference in performance.

The use of Hortonworks is free there’s no license but if you want there’s a support. It’s up to you to see if you need it (certainly) and to maybe negotiate it.

I did not really made the choice, as the client made it dependent on their experience, functionality of each distribution, privacy of the data and the licensing/support price.

Firstly perform a POC to learn and to get an idea of the load of your future applications. Then, you should be able to correctly design the need infrastructure.

The features I've found most valuable are--

• Ambari UI
• Hive
• Pig
• Hive
• Also integrated Tableau with this distribution

It's easy to deploy and we've used this distribution for some of our recommendation and trend analysis use cases.

I've used it for almost one year.

No issues encountered.

No issues encountered.

We faced some issues while upgrading to newer versions with current distributions, but with their support we solved it.

Customer service is great.

Technical support is great.

No, we did not use a previous solution.

Initial setup was straightforward.

We implemented it with our in-house team.

From a product standpoint, their Ambari UI is incredibly valuable for cluster monitoring. It simplifies the deployment and maintenance of hosts, and we can provision, configure and test Hadoop services.

From an overall perspective, Hortonworks support is crucial to our operations.

As this is open source, there are certain features that need tuning, such as the Hue UI. More stability on this would be helpful.

I've used it for one year.

As this is all new technology, we face issues at every level. However, hardware support and documentation have been instrumental in helping us resolve the majority of those issues.

We've had some issues with stability, but hardware support and documentation have helped us resolve most of those.

No issues with scalability.

They have outstanding customer support. Their responses are prompt, and they resolve issues quickly.

I have not used a solution of this nature before.

The set up is straightforward enough, but at every level there are many parameters to be tuned. Ensuring all these parameters are set is the complex part, as poorly set parameters can cause unwanted issues.

We have an in-house team to do implementations. I would advise that all implementations get seen through all the way to having users smoke test applications to ensure correct functionality.

I would suggest that if you are implementing this at an enterprise level, the support is compulsory. Additionally having a high degree of patience is key, as this is open source and road bumps can be frequent when moving at a fast pace.

Hortonworks is 100% Open Source. Hortonworks does a great job in managing all different components of Hadoop.

We've done multiple implementations of it. It enables customers to perform sentimental analysis from social media data to engineering analytics.

Security- Although they support Knox and Ranger and Kerberos, they are still missing attribute-level encryption features.

Name Node High Availability is still not stable (memory issues).

There are several features that are most valuable for us--

• Hue
• Hive
• Spark
• S3

With it, we have faster processing times for our apps.

It needs to be quicker and to have the ability to automate deployment on multiple nodes.

I've used it for two years.

Sometimes there were issues.

Sometimes there were issues.

Sometimes there were issues.

I've not had to use it.

No solution had been used previously, but we are using it alongside AWS EMR.

It was complex to configure.

It was done in-house.

We provide services for product implementation, so people looking for such products can contact me.

A few of them, namely: Hive/Tez, HBase, Ranger, Yarn and Ambari. Ambari helps managing the platform, Hive is very easy to use. Ranger for security; with Ranger we can manager user’s permissions/access controls very easily.

We have successfully ported a Microsoft SSIS product application into Hadoop, that saved millions of dollars for the company and, at the same time, they are getting better performance. Also, we implemented fraud detection, as quickly as possible, for the online orders. (Fraudulent orders became a big headache for our company. The early detection of fraud is saving the company a lot of money).

Hive performance. If Hive performance increased, Hadoop would replace (not everywhere) traditional databases (Oracle/Teradata, etc.), which would save a lot of money for the company.

I have been working on this HDP platform since Jan 2015.

No, our company is a satisfied customer.

No, not at all.

Product is good. Reason I gave a rating of eight is that their community is very large and relatively very quick in bug fixes.