Cloudera Distribution for Hadoop Reviews

It is a good enterprise platform. It is easier and more stable. Additionally, it has the best proxy, security, and support features compared to open-source products.

The areas of improvement depend on the scale of the project. For banking customers, security features and an essential budget for commercial licenses would be the top priority. Data regulation could be the most crucial for a project with extensive data or an extra use case.

We have been using Cloudera Distribution for Hadoop for a few years.

I rate the product’s stability a ten out of ten.

We have ten customers using the product. They include data engineers, performance engineers, and environment engineers.

I rate its stability a ten out of ten.

The product has a support subscription for one year. We use technical support only for complex use cases. We work with their team as we have direct and quick access to contact them. It helps us better understand the technical and business-related queries of the customers.

The on-cloud version is easy to set up. Although, it is complicated to process a large amount of data for on-premises or hybrid setup. It is not a ready-to-use solution for telecom or finance technology. It requires the deployment of robust technology relying on network infrastructure.

The product’s price depends from project to project. It is more expensive than open-source solutions and could be cheaper. However, in some cases, it is less costly than open-source.

It is the best solution in the world at the moment. I advise others to go for it if you have an enterprise customer. I rate it a ten out of ten.

We used this solution as a data platform. 

The pricing needs to improve. If the price was affordable, then we might have continued using Cloudera. We switched to HPE because of the cost.

I used this solution for the last year.

The solution is stable. 

It is a scalable solution. There were about 20 users of this solution in my company. 10 people were required for the deployment and maintenance of the solution, including developers. 

The initial setup is straightforward. 

The price is very high. The solution is expensive. 

I would recommend this solution to others.

I rate this solution as an eight out of ten. 

I use the solution because my data is too big. It is almost 100 TB.

The product provides many APIs to connect with other applications. The product provides better data processing features than other tools.

The dashboard could be improved.

I have been using the solution for seven years.

The tool is stable. I rate the stability an eight out of ten.

The tool is scalable. I rate the scalability an eight out of ten. It is easy to scale the product. Almost 20 to 25 people use the tool in our organization. We maintain the solution ourselves. We have nine engineers in our maintenance team.

The support is very, very helpful.

Positive

I have worked with Oracle. Oracle is too expensive.

It was pretty easy to install the product. It took us 20 minutes.

The product’s cost is higher compared to other tools. The pricing must be improved.

I recommend the solution to others. Overall, I rate the solution an eight out of ten.

We use Cloudera Distribution for file storage. 

This solution is deployed on-premise. 

The file system is a valuable feature. 

The security of this solution could be improved. There should also be a way to basically have a blockchain enabled storage with the HDFS. 

I have been working with Cloudera Distribution for Hadoop for 11 years. 

This solution is stable. 

This solution is scalable enough for us. 

We have created a product, using HDFS, and when our engineers install it for themselves or for customers, we use this solution. There are about 15 to 20 people using it at any point of time. 

The installation is straightforward. We use command-line-based installation and we have created our own way of installing with our product. 

Depending on the customer or depending on internal usage, our DevOps engineer will install it or my development team will install it. 

We are very well-versed on these tools, so we implemented it ourselves. 

I haven't bought a license for this solution. I'm only using the Apache license version. 

I rate this solution an eight out of ten. Cloudera is a great product and, overall, there are many features. 

We actually use Cloudera HDFS underneath, and we build our product on top of it. So, we don't use the Cloudera versions of all the other products, we just use the Cloudera HDFS, nothing else.

• Cluster rolling restarts 
• Cluster wide configuration management

For the clusters using CM, we are able to more tightly control and manage the configuration of all nodes in the clusters. 

We are currently running six production clusters totaling 900+ nodes, and are building three more clusters. Knowing that if someone has some custom configuration on a node that they haven’t communicated out, and that I can ignore that configuration and bring that node into line with where we’ve decided to run the cluster, is very beneficial.

HBase 1.0 stability issues and processing speed is a major area for improvement. Right now, our Cloudera 5 clusters run four to seven times slower than our Cloudera 4 clusters using our storm and kafka topologies, which causes real-time processing to be a major challenge.

CM’s API is very limited and difficult when used on multiple clusters in the same CM instance

We've used it for approximately two years. We also use Cloudera Manager, which is 6/10.

No issues encountered.

Cloudera 5 is currently very unstable. Between two Cloudera 5 clusters, we have an incident at least twice a week due to what are now outstanding bugs.

It's very easy to deploy and scale as large as you want. Once created on the CM management cluster, is difficult to scale up as needed, as you add more clusters to the same CM instance.

No previous solution was used.

We were already running one production cluster with approximately 75 nodes when I joined, so I’m not familiar with what was needed to get the initial production cluster up. Once I joined, I assisted in standing up the additional nodes and clusters using our chef automation.

In house via chef automation. Chef, or similar systems, makes it much simpler to stand up large scale clusters. That said, I have not used or evaluated vendor team implementation methods.

We mostly use the solution for big data analytics, data sharing, and reporting.

Cloudera, as a whole, is designed to provide organizations with solutions for big data. Cloudera is not one single component. It has many components related to storage, analytics, queries, and processing. All of these components work together to support big data implementation and analytics.

The performance of some analytics engines provided by Cloudera is not that good. So, we are using other analytics tools besides Cloudera.

I have been using the solution for more than four years.

We also use other tools like DataIQ and Apache Kudu.

I'm working with the solution myself. As a company, we are implementing it for other customers. Cloudera itself does not provide analytics. It prepares data for analytics tools that work with Big Data, such as Apache Spark, DataIQ, and Tableau.

Overall, I rate the solution a nine out of ten.

We are dealing with data from the telecom industry. We were using an Oracle system but our volume has increased. We now have a lot of real-time data that needs to be transformed so that it can be made available and used.

The most valuable feature is Impala, the querying engine, which is very fast. We have been able to work with one terabyte of data in less than 20 minutes. The speed makes it easy for us to process all of the data that comes in, in time.

The support is very good.

All of the data has automatic triple replication in order to secure integrity.

There is a maximum of a one-gigabyte block size, which is an area of storage that can be improved upon.

When we are upgrading CDH, there are many things that need to be upgraded and it would be helpful if it were bundled. As it is now, we have to upgrade many different things separately.

I have been working with the Cloudera Distribution for Hadoop for around two years.

It is a stable solution.

The scalability is good and it works on commodity hardware. One of the problems we have right now is that there is a lot of data and we're moving it from our Oracle solution. This means that there is a double cost, in terms of storage, during our transition to working with big data.

We are using a data lake that is a store for all of the data in our organization. There are more than25 projects, with between 25 and 30 people in each one, for a total of almost 1,000 people. All of them are dependent on this solution.

Most of our users are technicians who have problems to solve using the data available to them. A couple of them are data scientists and the remainder are upper management, who do the analysis.

The technical support is very good. Whenever we open a ticket, we get support right away.

We did use another solution prior to this one but it could not keep up with our increase in data.

This suitability of this solution depends on the size of the data that you are going to be working with. If you have going to be working with a huge dataset that contains many gigabytes of data then this is a good solution. For smaller datasets, you should also consider other technologies.

My advice for anybody who is implementing this solution is to take some time to learn it. Beyond that, be sure to contact support if you have any problems because they are very helpful.

I would rate this solution a seven out of ten.

We use this solution to process data.

When using an SQL Server you have to build indexes and you need to fine-tune the data.

We import the data that is in the SQL Source.

With a single script, we are able to run the jobs within minutes, which is an advantage.

We are using the Power BI model for the business convention. The performance in Power BI will be reduced if you incorporate more calculations. Those calculations are captured in the Hadoop layer and processed.

It could be faster and more user-friendly.

I have been using this solution for seven months.

It's a stable product. I don't see any performance issues.

This solution is scalable. We have 40 users for different projects in our organization.

We will continue to use this solution.

Technical support is good.

I didn't use any other product.

The installing is straightforward.

Our clients provide us with the access to use it directly.

Once you have been given access to the edge nodes we are able to run the scripts in the Hadoop layer.

We do not pay for licensing because our customers forward it, so there is no need to purchase the license for the project.

I would recommend this solution.

I would rate Cloudera Distribution for Hadoop a nine out of ten.