Cloudera Distribution for Hadoop Reviews

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.

I'm part of the IT team at my company, and our primary use case of this solution is building infrastructure for advanced analytics, where we copy data from our data warehouse that is now our relational database. We copy it to the Cloudera Distribution for Hadoop and then analyze it with Python and machine learning. 

The features I find most valuable is that the solution is that it is easy to install and to work with. It starts with the installation and from there on the management is very simple and centralized.

I would like to see an improvement in how the solution helps me to handle the whole cluster. For example, when I'm going down to a specific tool, like Kafka, for example, the Cloudera manager doesn't really help me. Then I have to use Google with other Kafka knowledge and tools. 

It is a very stable solution.

Not many people are currently using this solution at my organization, but I do believe it is scalable. I don't, however, have experience with upgrading or adding users. 

My problem is that I started using Cloudera Express without technical support and then I purchased the Enterprise edition through another company. So now I don't really have access to Cloudera support, even though I hardly need to use it. 

The initial setup was simple, but we had trouble implementing the cables in the Hadoop solution.

I had a bad experience connecting the Cloudera Distribution for Hadoop cluster to my other resources in the company, like the active directory or firewall. I would like to see the outside environment to be easier to handle. I will rate this eight out of ten because the solution doesn't cover everything. It is a very complicated solution because it contains a lot of internal tools. 

Mostly HUE, Impala, Sqoop, and Hive. The impala-shell command is number one.

We are working on research for genomic data looking for specific genes and variances. Even Hive was not good enough to process it correctly, only with Impala are we getting results quicker.

Sometimes the heavy queries do not finish at all. It would be good to see the progress of heavy script in the impala shell or get some way to access it.

We started to use Cloudera about one-and-a-half years ago.

We are having some issues with stability and are speaking to Cloudera support.

It's acceptable.

It's acceptable.

We were trying AWS Impala as well, but Cloudera won as it had more functionality with HUE, Sqoop, and Solr as built-in functions.

We have struggled a bit in installing and configuring Cloudera Manager on the AWS cluster. For now, it is good.

We did the implementation only using our team and resources. It was a hard start, but an easy landing.

Cloudera is good for mid to big company, but small ones can use AWS Impala/HUE. Go to training, or you are going to spend many hours to find short answers. The Cloudera solution is big with good documentation, but you need to know what and where to read first.

Faster runtime for batch jobs.

Improved Business Intelligence reporting from daily to every two hours satisfying the business stakeholders who would favour transactional systems to draft reports because it had the latest data. 

The issue that arises using transactional systems with multiple version of truths across the enterprise. With faster turn-around time business stakeholders are now adopting the BI systems designed to give a cohesive view of the performance metrics important to them.

Full Support for all Spark SQL features, support for SparkR, compatibility with Hive for DataFrame saved tables.

Cloudera CDH5.5.x does not support SparkR. SparkR, the integration of R models in API would be a great addition since this will enable fast near real-time analytical integration of R models with data feed.

The functionality in SparkSQL to save a DataFrame as a table in HIVE produces a table not compatible with HIVE. There is a workaround for this in creating the HIVE table first and then doing inserts.

Cloudera CDH5.5.x is a great product, but the adoption of additional features not currently supported will make the product even better but by no means subtract from its desirability.

Do thorough research and ensure your use-cases or scale does not conflict with the system requirements and that those features that would make a difference are supported.

This product is a framework for edge AI, it comes with multiple ecosystems as a project. I'm a senior data architect manager and we are consultants. We offer Cloudera to our customers but we don't have a partnership with them. 

The best feature is the layer shared experience. If you have a cluster available on-prem or in the cloud, you can manage that security layer using the shared SDX and it provides flexibility. New features are constantly being added. 

The only thing that needs improvement is the cost, it's a very expensive solution and one of the main reasons companies are not attracted to the product. 

This product has been around for a long time so it's very mature and stable.

The scalability is very good. 

The initial setup has become easier although you need a dedicated admin to maintain and manage the solution because it's a framework and not a single product. Deployment nowadays is much smoother with the PaaS offering in the public cloud, so you can carry out the deployment with an in-house team. The deployment only takes a day but a company is unlikely to go with the default so the solution needs fine-tuning which can take a couple of weeks. 

For enterprise organizations that can bear the cost, it's a good solution. A smaller company wouldn't be able to afford the licensing fees. You can get a free trial for 60 days. They'll never have a community version because they're the only ones in the market offering this kind of framework. 

I rate this solution nine out of 10. 

I've been working on the software installation from the beginning, and we have a client for global supply change, so we get information from Telefonica's sales and distributions. Getting all that information into this system allows us to process it, get KPIs, and create outgoing information for business intelligence tools. 

In the cloud provider enterprise we get all the information from the gamers, like delays, response, and information from the games. It allows us to see if gamers are having trouble, high latency or any other kind of issue. They test that and get information about the issues in order to solve them.

I like the combination of all the tools that allow me to provide solutions and enable me to solve the use cases I'm working on. You need tools or components to foresee everything, and they are all in our emails. Sometimes you try several of them, and sometimes one will work better than the other. So you have to test the tools to see what works for you. 

We experienced many issues when we started working with Hadoop 3.0 in the Cloudera 6.0 version, so there are a lot of things that need to improve. I believe they are working on that. 

It's been quite easy to install. We only had to follow the instructions and there weren't many problems. That's important for us.

I will rate this solution a nine out of ten because nothing is ever perfect. You will always face problems, but I'm quite happy with Cloudera. 

The Cloudera Manager administrator webpage simplifies the administration tasks and helps to maintain a global overview of the cluster performance.

We are moving from an standard SQL environment (Oracle DataWarehouse) to a Big Data environment, and the Hadoop cluster will be the key of our new organization. It will allow to scale in an easy namer.

We found some difficulties when importing Hive tables from another Cluster.

I want to point the fact that we encounter many problems related to the cloud storage and how resources are managed. Our learning has been that, although it is quite simple to deploy single machines on the cloud, deploying clusters of machines is much more complex as many factors need to be considered: individual machines, connectivity across machines, storage.

I've used it for three months.

We found some issues but were related with the hardware provider. For the moment I have not detected any problem from the Cloudera software point of view.

Technical support is really efficient.

We chose this product as it is considered a market standard and due to its wide documentation on the web. I evaluated other options but the fact that now it is becoming an standard for many companies helped me to choose this option.

In the cloud environment where we deployed (Azure Resource Manager) there was a ready-to-deploy template which simplified a lot the initial set-up.

We implemented with an in-house team. Our initial idea was to stop the cluster during the weekends and when there was no usage. However, we found strong difficulties and we were not able to start programmatically the whole cluster, so finally we left the cluster working all the time.

This issues were mainly related with the cloud provider and how this provider manages the resources for the cluster machines.

From our point of view it is a long-time investment. We hope to get the ROI in the following years.

I am very comfortable with this product. The combination of Cloudera Manager administrator server, which allows the management of the Hadoop Cluster, and the Hue server, which simplifies the use make this product a current standard on the market. Perhaps it lacks a full integration of all its components.

We are a distributor for Hadoop. Our customers choose whether they would like to use Cloudera or another product.

Cloudera Distribution is deployed on-premise as well as on bare metal servers in AWS.

Cloudera is a very manageable solution with good support.

When you compare Cloudera with EMR, EMR has a lot of administrative features, so you don't need to manage the solution. Cloudera is not as easy, as it requires more DevOps resources than other solutions.

We have been offering this solution for five years.

Cloudera Distribution is stable.

This is a scalable solution. We have clients that have a large installation of Cloudera.

Technical support from Cloudera is fine.

The initial setup of Cloudera is difficult. After you have installed it once, it is not difficult to reproduce.

For a POC deployment, we required only one DevOps. On larger-scale implementation, we also require a data engineer. 

Cloudera requires a license to use.

We looked at EMR, however Cloudera is better when using OnPrem.

Cloudera is one of the best solutions for on-prem. 

I would rate this solution an 8 out of 10.