Cloudera Distribution for Hadoop Reviews

• Cloudera Manager for administering the Hadoop cluster
• Cloudera specific solutions like Impala
• Extensive documentation
• Good user community

Implementing a Hadoop cluster has become relatively straight-forward using CDH. Administering it is also less complex. As a result, efforts spent in these areas are less than anticipated.

• Some of the UI features seem confusing e.g. charts on the CM Services page
• Sometimes it gets confusing to follow a single path for installation due to multiple recommended approaches e.g. parcels vs packages

We have been using it for the last two years.

Following a single path for installation becomes confusing due to multiple recommended approaches e.g. parcels vs packages.

Flume seems unstable and has to be restarted quite often.

None as such

We are mostly using Cloudera Express so we did not use their technical support. However, the Cloudera community is an active place and Cloudera representatives participate actively in understanding and resolving issues.

Cloudera is a prominent player in the Hadoop space and we did not have a need to adopt a different solution. However, we are also looking to work on Hadoop and MapR

Following a single path for installation was initially confusing due to multiple recommended approaches e.g. parcels vs. packages. However, after a while, we managed to master it. However, knoweldge of Cloudera Manager and Hadoop architecture is a must.

We have our own team of consultants who are proficient in implementing it. The high level steps about the implementation remain the same; however, it is the environment specific issues which are challenging.

We haven't really measured ROI.

Licensing price on per node basis for Cloudera seems to be pretty steep (based on the inputs we have received from Cloudera).

It is user friendly and installation is pretty straightforward. Cloudera Manager is a good tool to administer it. However, configuration for specific requirements is sometimes pretty complex.

You should have a team which is knowledgeable in Hadoop. Do keep in mind that the product is still maturing so there are good chances that you will come across unexpected issues now and then.

Very solid. Excellent user experience. good documentation. The Cloudera Manager is definitely a deal breaker. Packaging for Ubuntu is great for all the components.

Before the introduction of Cloudera Manager (that actually works), all the orchestration was done with scripts and Chef, and inexperienced team members had difficulties to participate in maintenance. The Cloudera Hadoop manager eased the work.

More customization, better documentation for the API (basically it's the same for all Cloudera Hadoop components).

I've used it for two years.

No issues encountered.

No issues encountered.

No issues encountered.

Didn't use dedicated service or support. The documentation is a bit of a mess, but it is decent and sufficient.

Straightforward. The CDH VirtualBox with preconfigured environment helps for demonstration purposes

We did it in-house.

We also looked at Hortonworks, but chose Cloudera because of my familiarity with it.

Do a comparisomn with Hortonworks as it's always good to compare to another major vendor

The most valuable feature for me are--

• Sentry - provides granular-level security
• Impala - open-source, MPP database

We used it to build an enterprise data hub.

Apache Kudu needs improvement. It's a real-time updatable database.

We used a vendor team to implement the solution.

We use the solution for the data warehousing.

The product as a whole is good.

There are better solutions out there that have more features than this one.

I have just started using the solution.

I do not know of any issues with the stability of the solution.

I have an internal team that does maintenance for the solution.

The price could be better for the product.

Enterprise resource management, ease of use in terms of integration within the Hadoop ecosystem related products, and security.

Mainly they have to continuously evolve following the technology trends and replace or adapt part of their solutions accordingly.

We've used it since October 2012.

No issues encountered.

No issues encountered.

No issues encountered.

Pretty responsive and reactive compared to their competitors in the field.

It was extremely easy, and allowed less experienced personnel to get into the context pretty fast. Any difficulties/complexities faced were not related to the product itself rather than to the cluster infrastructure used.

In our case it was an in-house team including data scientists and data engineers (management & QA as well). With the appropriate training and the support offered by the vendor, it is not that hard to implement a small to medium scale project solution. However, complexity and size varies significantly between projects; therefore, it really depends.

That is not easy to answer since Huawei has several divisions using the product in different ways. Again regarding pricing/licensing highly depends on the context and the aims of the given organization for instance the level of support they are going to need, the type of services they are going to provide, or even the business domain they are targeting.

There were two provider solutions that have been evaluated. However, the level of customer service and technical support from Cloudera was better than the first one, and the second solution licence pricing was higher compared to Cloudera’s pricing schema.

Cloudera is doing a great job in the field offering an enterprise ready data platform. Based on my experiences I would definitely recommend it.

Our primary use case for this solution is to host a big amount of data in our platform, processing, analysis and all of this stuff on the platform.

Cloudera is always developing new tools and supports a wide range of tools. We also really like the Cloudera community. You can have any question and will have your answer within a few hours. Cloudera is better than other competitors because they acquired Hortonworks.

We're processing a huge amount of data on our system. Without the big data environment, we cannot store all of this data live. We have billions of records and terabytes of storage to be used. It's not an option actually for us to have a big data environment. Cloudera is trying to adopt new technologies.

I think the idea of open source tools now is dominating. So Cloudera has to decide how to deal with open-source tools. I subscribe to Cloudera to get an enterprise version but I have found that I can get some of its features from other vendors that would be at a lower cost than Cloudera. They should lower the price. 

We have been using Cloudera for a year. 

It's stable. I have no issue regarding the stability.

It's scalable. You can add more nodes and you can expand your cluster easily.

After we open a ticket, the issue can be resolved very quickly, they have a management portal. I don't contact them directly, but I haven't heard anybody having any problems with it. 

The initial setup is complicated. We needed the vendor to install it themselves. The deployment took around three weeks. Three people were involved because they just follow up and supervise the deployment, but they're not deploying anything. The vendor does it. 

In terms of the advice, I would say to focus on what tools are available on the market. In terms of open-source, most companies are delivering open source technologies and providing support to these tools. Now I have the option to purchase a license for whatever platform for $1. I can deliver it with another small company at a lower cost. If I was the decision-maker, I'd invest in open-source tools. Cloudera and all of these companies are trying to adapt to these big data technologies and open source tools. Cloudera is trying to put it inside their platform so that we can have a compatible solution.

I would rate it an eight out of ten. 

Our core product is an insurance product and the actuarial module is quite complex. SMEs so far collect data from various sources into Excel sheets and through macros do the analytics which is a very crude form of doing the analysis. So we thought to use big data for such analysis.

That is still in PUC stage, as I have mentioned our analyst used to do the actuarial on a spreadsheet but after Hadoop  implementation they are getting confidence that now analysis is more appropriate and fast. Now exploring cloud implementation as well.

Keeping multi copies of the file and tools of map reduce like PIG, HIVE due to their flexibility it is easy to develop the application with less or almost no knowledge of Java and Sql. And capability to handle huge data size.

As such in the product side, I don't have much to comment. But like other upcoming technologies like RPA, AI, GO etc they have ample training materials with variety of USE Cases, which users can understand and aligned with their current requirements. On same ground I didn't see much training materials from Cloudera.

Seems quite stable, as such didn't face any issue.

It is very stable, didn't face any performance issue.

No when we were heard of Hadoop, we tried on that only. I mean tried to migrate from spreadsheets to Hadoop.

Very straight forward. Typical Windows type installation...Next, next, next clicks.

In-house.

Other department handles all these so I can't comment on that.

Not really.