Cloudera Data Platform Reviews

We use this solution for the hospitality industry. 

It was for end to end data processing and data manipulations.

The data platform is pretty neat. The workflow is also really good. 

The NiFi platform could be enhanced. This refers to the data ingestion in a workflow. 

It would also be nice if there was less coding involved. 

I have been using this solution for six years. 

The technical support is okay, but not excellent. They can take a while to respond. 

If you wish to use this solution, make sure you compare it with some other solutions first to make sure it's right for your needs. 

Overall, on a scale from one to ten, I would give this solution a rating of nine.

We use this solution to look at and manage big data. It's mostly historical data that we offload from our data warehouse, as well as from other databases in other platforms.

We have two different installations. The first one is based on IBM POWER CPUs, and the other one is based on Intel CPUs. Our data center is on-premise. There is some thought on moving to a private could, or a private IBM cloud, but we have not proceeded with that as of yet.

This solution is a cheaper way for us to offload the otherwise expensive data. We can move data from outdated database versions, such as Oracle 10. It is now out of support, but still hosts some of our historical data. This solution has helped us move our data to the current version.

Previously, we had our data on more expensive platforms. Now, using this solution, it is much cheaper to have all of the data available for searching, not in real-time, but whenever there is a pending request.

We have had problems with the backup and with services that require a disaster site. We are still struggling with some of these issues.

We are having trouble with Active Directory and Hive integration.

I would like to see more support for containers such as Docker and OpenShift.

We have had some issues with the code, but it's mostly from the developers. From our side, we don't see any issues with stability, although it may be that we have a lot of unused CPU capacity.

We have not acquired any additional hardware since our initial purchase. However, we expect more use cases to be added, at which point we may have performance or scalability problems.

The initial setup is not very difficult. The configuration is not easy, but somebody with some experience is able to set it up. We had users for which we had to set up quotas and queues. For us, the basic installation was completed within a matter of a week.

We had IBM set up both of our installations. 

This is a good product, but we still have some issues with backup, and the performance monitors that we install on every system. There may be solutions, but we're struggling to integrate them.

This is a product that I recommend. It's a solution that comes at a lower price, and it works well if you don't have expectations that it will behave like a much more expensive system.

I would rate this solution an eight out of ten.

We use it for data science activities.

Data is now available.

I have no preferences towards any feature.

• Security
• Performance
• Workload management

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.

• Ambari Web UI: user-friendly
• Views for Hive, Tez, Pig
• Spark and Ranger

It has helped our organisation cater to clients who are using Big Data for data storage and analysis combined with our security product.

Deleting any service requires a lot of clean up, unlike Cloudera.

Five years.

Not until now.

No.

Very supportive, prompt responses.

We didn't use a previous solution.

The Ambari upgrade is not very user-friendly.

Not applicable.

Cloudera and MapR.

It's a great company with a great product employing dedicated people.

We evaluated Cloudera and Hortonworks. Based on our evaluation and actual experience in production of 60 nodes and development of 12 nodes, the most valuable features of Hortonworks are:

• 100% open
• No lock-in like Cloudera
• Fast and accurate support instantly
• Largest number of committers to Hadoop by any means
• Hive is better in performance and ease of use compared to Impala

It helps a lot in data in motion (ingestion and manage in real time). We are able to do 3rd-party data monetization of our data within a t+20 minute time frame to our end customers.

• Cost
• Reliability
• Speed
• Ease of use

I have used it for three years.

I initially encountered deployment issues, but they were very good in resolving them.

I have not encountered stability issues.

I have not encountered any scalability issues at all. That's the key reason we picked HDP over Cloudera, as Cloudera have issues & don't support compression of Hive in ORC format. They push only their products (not good).

Customer service has been excellent from the day one until now... and our Admin is comfortable with the SLA and turnaround time.

Technical support is very good and proactive with SmartSense.

We previously used a different solution. We switched from Cloudera. Initially, we went with Cloudera due to it being a popular choice in the market, etc, then realized it was bad choice. Before we scaled from 6 nodes to 12 nodes and before we went livein production, we scrapped it due to Impala's performance and lock-in.

Using Ambari, it was easy to set up and we even tried the AWS for a test cluster.

An in-house team implemented it: two admins, seven developers, one data scientist, one PM and 22 business users at the customer (end-user side).

ROI is 300%.

Hortonworks is the best, comparing all three flavors. If all is well, we might use open source alone in the next three years; others you can't due to lock-in...

Before choosing this product, we also evaluate Cloudera.

It is the best in terms of product vision and actual delivery.

• It's the one and only complete open source big data platform
• Ambari-managed admin configuration for HDFS, YARN, Hive, HBase, etc.
• Customized dashboards
• Web-based HDFS browser
• SQL editor for Hive
• Apache Phoenix - OLTP and operational analytics on Hadoop
• Apache Zeppelin - A web-based notebook that enables interactive data analytics

• Maintenance of our own data lake in the enterprise-level
• Storage and analysis of server logs
• Applying Operational Intelligence in the enterprise-level based on the analysis of various department units data
• Semantic analysis based on the feeds from social networking data, clickstream data, etc.

• Rolling upgrade
• Disaster recovery features such as mirroring should be supported

We've used it for one year.

No issues encountered.

No issues encountered.

No issues encountered.

3/10

3/10

No previous solution was in place.

It's easy to setup.

We did it in-house.

Completely use the community edition along with other features that can be implemented on top.

No other solutions were looked at.

Study, analyze, and compare with other big data platforms features according to your requirements before choosing the appropriate one.

It has a powerful, user-friendly interface called Ambari which allowed us to administrate our cluster easily.

It allows us to performa data lake implementation to handle/treat huge amounts of data, or what we call the "terrible bytes”.

Integrate a complete hive web client (Ambari views), like Hue Today, in the next release.

I've used it for three years.

The HDP v2.3 is stable release. But we have encountered some issues linked to hbase (fixed by: hbase server and region server should not be installed on the same node).

It has good documentation, but it's not fully complete for complex security needs (knox/ranger with cluster).

We have installed our first cluster using native Apache repositories.

The setup of Hadoop was easy thanks to Ambari, but installing the security components was complex.

Our cluster has been implemented in-house. We have automated the entire installation of Hadoop, set-up and configuration included.

Hadoop/Cloudera is still much cheaper than Oracle's RDBM system, if you want to handle a huge amount of data and make complex analytics. 

It's 40,000€ for 10 Hadoop nodes vs 1.7 million Euros  for an Oracle server with 40 cores.

In short, I recommend this product simply because Hortonworks is the only distribution that runs on Linux and Windows Servers.