Amazon EMR Reviews

We primarily use the solution for tech processing. 

It's made life very easy. Now, a lot of things are very automated. 

It is easy to manage. The applications are much easier as compared to others.

The solution is pretty simple to set up. 

It's stable and reliable.

The product can scale. 

The cost is increasing. We are looking into how we can optimize the cost part of EMR. We're doing a comparison between Cloudera running on AWS and running AWS EMR.

We don't have much control. If we have multiple users, if they want to scale up, the cost will go and increase and we don't know how we can restrict that price part. 

I've been using this solution for a while now. It's been maybe a year or more. 

It's quite stable. There are no bugs or glitches and it doesn't crash or freeze. It's reliable. 

The product can scale. It's not a problem at all. 

Technical support is okay. The only challenge that we face is when case we integrate with other open-source solutions or products. We have issues, for example, with integrating ranges, and the VMR.

We are also using Hortonworks, which is now a part of Cloudera.

The initial setup was very easy. It's not overly complex or difficult. 

We can deploy the solution in a single day. It's very fast to get up and running. 

There's a team of ten people that can handle the setup and maintenance of the product.

We have a team that handles the initial setup.

The ROI would depend on the business case. I can't speak to an exact ROI. 

The price can get a bit high. We're looking for ways to reduce costs. 

Right now it costs us between $40,000 and $50,000 a month.

We are a customer and end-user.

I'd advise potential new users to give it a try if they have the requisite use cases. If it fits their use case, they should definitely go for EMR.

I'd rate the solution seven out of ten.

We are using Amazon EMR for big data processing. We have a client which has financial data and we are using a big data framework to process the data. Amazon EMR is providing all these features needed and we are using Amazon S3 for storage purposes.

We are in the process of moving many aspects of our processes into clouds, such as AWS Managed Services for metrics. We want to migrate our graph and many other aspects to Amazon AWS.

In Amazon EMR it is easy to rebuild anything, easy to upgrade and has good fault tolerance.

Amazon EMR can improve by adding some features, such as megastore services and HiveServer2. Additionally, the user interface could be better, similar to what Apache service provides, cross-platform services.

I have been using Amazon EMR for approximately seven years.

Amazon EMR has high availability for storage services or insurance processing engines. They have a guarantee of the data and availability. It is a highly stable solution.

Whenever we have scaling policies for load balancing and our load increases the input rate, we increase the resources. However, at that time Amazon AWS is not providing the scale of the required resources in a short time. It takes too much time to allocate resources, such as increasing the upscaling of the instances. The time overhead should be reduced. There is a performance issue between the cloud and on-premises.

There is some problem that we have not pinpointed yet, but there is computing power that is not up to the standards.

We have more than 1,000 people using this solution in my organization.

I have contacted the support on a regular basis. They have been responsive with a solution.

I rate the support from Amazon EMR a four out of five.

Positive

The initial setup of Amazon EMR is very easy. The time it takes for the full deployment of the solution depends on our Terraform script. However, it typically takes a maximum of 30 minutes to deploy any cluster.

The price of the solution is expensive.

When comparing this solution to others there are three to four features that are more attractive rather than others. It's user-friendly and easy to deploy.

My advice to others is to use the free version of the solution and make their decision to purchase it afterward.

I rate Amazon EMR an eight out of ten.

EMR is used to analyze data for projects where we wish to ingest multiple data sources into our analysts' data lakes. EMR is further used to process millions of roles within a fixed span of hours.

It gives us multiple options from Infra to the WES and different tools. It has a variety of options and support systems. Plus, it makes life easy for our developers, whether in the cloud or on-prem. Related DevOS installations are quick and easy to maintain.

Interdependencies with a third-party or open source solution should be improved. Modules and strategies should be better handled and notified early in advance. Maybe if AWS starts releasing AWS-certified or AWS-verified installations, that will generate even more confidence just like OpenJet, it'll add a specific version. 

I have been using Amazon EMR for three years. 

The solution is mostly stable with certain data and code related issues. 

Amazon EMR is a scalable solution. We have around twenty users, but they are engineering users. Outside, we have, our analytics product, which is being used for most of our clients. We have plans of upgrading the usage of the solution. 

The technical support team is good. The team is thorough with their knowledge and are quick to respond. 

The initial setup of Amazon EMR is straightforward if you know the basics and have knowledge of big data and architecture. The AWS documentation also helps with the deployment. Initially, the deployment takes a few hours and then it becomes easy. 

The maintenance depends on your application and specific requirements, but for deployment, you don't need a much bigger team, probably a team of one cloud guy should be enough.

The deployment can be done in-house. 

There is a small fee for the EMR system, but the major cost components are the underlying infrastructure resources that we actually use. 

My advice would be to do a dependency analysis to understand the limitations before planning to move in with Amazon EMR. I would rate the overall solution a six out of ten. 

We primarily use the solution for AWS services. For example, in a typical B2B project management, some coders are sequencing at different speeds and managing the overall ports from other coders. We deploy the solution on cloud.

We value the streamlined solution, and the project management is very streamlined using almost all the features.

We have had issues with the boolean mathematical operation in 2. X's big version is working in newer versions because the old version of the solution does not support it, which is a compatibility issue that can be improved. In addition, the legacy versions of the solution are not supported in the new versions.

We have been using this solution for six months.

I rate the scalability a seven out of ten, and approximately seven amazon users who are architects, project managers, and testers use the solution in our organization. We intend to gradually increase the usage in our organization by at least five to ten percent annually.

We have had a very good experience with customer service and support. I rate them a ten out of ten.

Positive

The initial setup is straightforward, and deployment takes between 15 and 20 days.

We implemented the solution through a vendor team.

We have not calculated our ROI.

The licensing costs are expensive. I rate them a seven out of ten, with one being the least expensive and ten being the most expensive.

I rate the solution an eight out of ten. The solution is good, but its compatibility with older versions can be improved. I recommend the solution to users considering implementing it in their organizations.

The product is deployed on cloud.

The product can be improved by automating their up-sizing and downsizing their cluster.

We have been using this solution for less than one year and are currently using one of the latest versions.

The solution is stable.

The solution is scalable.

I cannot rate customer service and support as we have not contacted them.

The initial setup was time-consuming, and deployment took approximately 30 minutes. In addition, one person was required for deployment and maintenance.

I cannot comment on licensing costs as I don't know the prices.

We evaluated IQ.

I rate this solution seven out of ten. The solution is good but can be improved by making it more user-friendly and easy to set up.

The solution helps us manage huge volumes of data. It is a major benefit.

The product must add some of the latest technologies to provide more flexibility to the users.

I have been using the solution for three years.

The tool is stable.

The tool is scalable.

I am very happy with the support team.

The installation is easy. It can be set up with a few clicks.

The product is not cheap, but it is not expensive. It is moderately priced. It is worth the money.

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

We use Amazon EMR to manage new data software like Hadoop.

Amazon EMR is a good solution that can be used to manage big data.

As people are shifting from legacy solutions to other technologies, Amazon EMR needs to add more features that give more flexibility in managing user data.

I have been using Amazon EMR for three years.

The solution’s technical support is good.

The solution's initial setup is very easy since it's all about cloud service deployment.

Amazon EMR is not very expensive.

I would highly recommend Amazon EMR to other users.

Overall, I rate Amazon EMR an eight out of ten.

A use case of this solution, for one of our clients with a large database of letters with addresses, is to predict if a person still lives at the listed address or if they have moved to another. We leverage EMR and SageMaker in AWS. 

EMR is cloud-based and managed through the cloud. 

One of the valuable features about this solution is that it's managed services, so it's pretty stable, and scalable as much as you wish. It has all the necessary distributions. With some additional work, it's also possible to change to a Spark version with the latest version of EMR. It also has Hudi, so we are leveraging Apache Hudi on EMR for change data capture, so then it comes out-of-the-box in EMR. 

Amazon EMR is continuously improving, but maybe something like CI/CD out-of-the-box or integration with Prometheus Grafana. 

I have been working with this solution for three years. 

This solution is pretty stable. 

It's managed services, so it's scalable as much as you wish. 

There are something like 40 to 50 people using EMR in my organization. 

We are an AWS Premier Partner, so we have all the necessary support and the ability to contact product teams. 

We didn't use any other products before implementing EMR. Some of our clients have Cloudera distributions, but we prefer EMR. 

The installation is straightforward because you can do it from the AWS Console or with Terraform. You can do it yourself. 

We implement this solution ourselves. On our team, we have admins, data engineers, DevOps engineers, and MLOps engineers. We have 40 or 50 data engineers. 

You don't need to pay for licensing on a yearly or monthly basis, you only pay for what you use, in terms of underlying instances. 

We have a range of clients in addition to the client with the large database of addresses. Another client is a large blockchain company and we do analytics for them, using Bare Metal and Hadoop, but not EMR. We're also doing Spark Streaming, Spark SQL, and some queries with Impala. We also have a company that enriches data from mobile companies, in terms of GAL locations of cell phones, with a variety of data from other sources to predict profitability.

I rate Amazon EMR an eight out of ten. It's continuously improving, and now it's possible to manage EMR directly from SageMaker Notebook. It's continuously evolving. I would recommend EMR to others because it's pretty straightforward, so onboarding doesn't take much time.