Amazon EMR (Elastic MapReduce) vs. Cloudera Manager

We are running it to perform preparation which takes a few hours on EC2 to be running on a spark-based EMR cluster to total the preparation inside minutes rather than a few hours. Ease of utilization and capacity to select from either Hadoop or spark. Processing time diminishes from 5-8 hours to 25-30 minutes compared with the Ec2 occurrence and more in a few cases.

Incentivized

Cloudera Manager is well suited for environments and deployments where the administrator user base is not well versed in the Apache Hadoop ecosystem or the Linux command line interface.

Incentivized

• The cluster size of MapReduce is very dynamic and therefore scalability is good for EMR.
• It also works well with other Amazon Web Services like Amazon Simple Storage Service, which means that data can be taken from those services and written back to them.
• I tried using the in-house hosting at the university I work in, but there would be a lot of complications with technical support required. For Amazon, the support and documentation was good to solve these problems faster.

Incentivized

• Cloudera Manager has an easy to use web GUI. You can start and stop cluster and services. It will start and stop services in a cluster in the right order. You can monitor the cluster, services, and physical host hardware as well.
• Cloudera Manager has an easy to use API that allows us to create scripts to automate deployment process.
• Cloudera Manager has an option to add additional services that you could manage via the web GUI.

Incentivized

• Sometimes bootstrapping certain tools comes with debugging costs. The tools provided by some of the enterprise editions are great compared to EMR.
• Like some of the enterprise editions EMR does not provide on premises options.
• No UI client for saving the workbooks or code snippets. Everything has to go through submitting process. Not really convenient for tracking the job as well.

Incentivized

• Support for third-party Python APIs within Cloudera Manager extension framework
• Providing more reporting/logging functionality as part of the open source distribution
• Support for the latest RHEL versions sooner in the release lifecycle

Incentivized

It meets all my customer's needs.

Incentivized

Documentation is quite good and the product is regularly updated, so new features regularly come out. The setup is straightforward enough, especially once you have already established the overall platform infrastructure and the aws-cli APIs are easy enough to use. It would be nice to have some out-of-the-box integrations for checking logs and the Spark UI, rather than relying on know-how and digging through multiple levels to find the informations

Incentivized

I give the overall support for Amazon EMR this rating because while the support technicians are very knowledgeable and always able to help, it sometimes takes a very long time to get in contact with one of the support technicians. So overall the support is pretty good for Amazon EMR.

Incentivized

Snowflake is a lot easier to get started with than the other options. Snowflake's data lake building capabilities are far more powerful. Although Amazon EMR isn't our first pick, we've had an excellent experience with EC2 and S3. Because of our current API interfaces, it made more sense for us to continue with Hadoop rather than explore other options.

Incentivized

I have not used any competitors, such as Hortonworks, because Cloudera Manager just works and meets all my customer's needs. I only have deployed Hadoop using command line, which is not easy to use and manage.

Incentivized

• It was obviously cheaper and convenient to use as most of our data processing and pipelines are on AWS. It was fast and readily available with a click and that saved a ton of time rather than having to figure out the down time of the cluster if its on premises.
• It saved time on processing chunks of big data which had to be processed in short period with minimal costs. EMR solved this as the cluster setup time and processing was simple, easy, cheap and fast.
• It had a negative impact as it was very difficult in submitting the test jobs as it lags a UI to submit spark code snippets.

Incentivized

• Cloudera Manager has allowed our organization to deploy Apache Hadoop to operations quicker and with less training versus using the command line exclusively.
• Increased employee efficiency.
• Increased product adoption.

Incentivized