Cloudera 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

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.

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).

• Ambari
• Hive
• Sqoop
• Flume
• Spark

The Hadoop value proposition is in expanded functionality, linear scalability, and reduced software and infrastructure costs. Hadoop offers several generic frameworks for batch, real-time, and iterative processing, such as map-reduce, spark, and spark streaming. Additionally, these frameworks provide libraries for predictive analytics and machine learning. This type of expanded functionality is not easily achieved on any other single platform.

File system to provide indexed access to individual records with in-place update/delete. Also, Security integration through a common interface for authentication, authorization, disk encryption, network encryption, data access layer, data masking, etc.

Hadoop, does not provide improved performance, compared to traditional RDBMS, unless processing batches in the TB-PB range, or if the Hadoop platform has significantly more resources available.

I have implemented various flavors of Hadoop over the past five years, including platform configuration and application development.

Deployment is improving rapidly, but like other flavors of Hadoop there are always issues.

Stability is improving rapidly, but like other flavors of Hadoop there are always issues.

5/10 - Responsive, but like all flavors of Hadoop, there are too many tickets to be reasonably triaged and supported.

I have implemented various flavors of Hadoop such as Hortonworks and Cloudera over the past five years, including platform configuration and application development.

Straightforward once you know what you’re doing.

I work for a vendor team.

ROI is one of the main reasons organization pursue Hadoop. Cost per TB is a compelling factor.

Hadoop is complex. It takes a dedicated approach from individuals with a broad range of technology skills and commitment to overcome challenges that do not normally present themselves in well-established technologies.

Hadoop is complex. It takes a dedicated approach from individuals with a broad range of technology skills and commitment to overcome challenges that do not normally present themselves in well-established technologies.

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.