Amazon EMR Reviews

Various viewpoints indicate that Amazon EMR's return on investment fluctuates depending on vendors and usage. Responses emphasize high returns, especially for those transitioning from on-premise systems, with expectations of at least two-to-one returns. Some report noticeable savings of up to 20%. While specific figures are often not calculated, and some can't provide precise return details, feedback suggests that it generally results in substantial cost efficiencies and savings for companies.

Enterprise buyers evaluating Amazon EMR find its pricing reliant on usage and integration, with costs mainly driven by infrastructure resources, particularly EC2 fees. Users appreciate the lack of additional licensing costs, but some note the service can be expensive compared to competitors. Cost control is possible with strategic resource management and careful monitoring, as unexpected charges can arise. Monthly expenditures can vary, with large enterprises spending significantly more annually based on their needs.

• "I rate the tool's pricing a five out of ten. It can be expensive since it's a managed service, and if you are not careful, you can run into unexpected charges. You can make a mistake that costs you tens of thousands of dollars. That's happened to us twice, so I'm sensitive to it. We're still trying to work on that. Our smallest client probably spends a hundred thousand dollars yearly on licensing, while our largest is well over a million."
• "The product is not cheap, but it is not expensive."
• "Amazon EMR is not very expensive."

Amazon EMR is utilized for running Spark scripts, building data lakes, and handling tech processing. It supports complex algorithms, data pipelines, large databases, and big data frameworks. Organizations migrate processes to the cloud, leveraging EMR for cloud-based management, serverless architecture, and data analysis. EMR is also used in industry-specific applications, data transformation, and integration with AWS services like SageMaker, Airflow, and S3.

Amazon EMR's customer service has mixed ratings, with some finding it great, while others find it inconsistent. Technical support generally receives positive feedback for being knowledgeable and responsive, though some users report slower response times when integrating with open-source solutions. Many users appreciate having access to responsive support, particularly when encountering urgent issues, and benefit from 24/7 availability and comprehensive assistance with technical inquiries, billing, and deployment activities.

Amazon EMR's initial setup is mostly perceived as straightforward, especially for users familiar with the tool and big data concepts. Some users find it complex due to configuration challenges and issues with multi-factor authentication. Deployment can be done quickly via AWS Console or Terraform. Initial setup duration varies, ranging from 30 minutes to several weeks, influenced by documentation use, team expertise, and specific project requirements.

Amazon EMR is considered scalable by several organizations, with capabilities to tailor clusters using memory, storage, or GPU needs. Companies expand usage gradually, leveraging auto-scaling, EC2, and on-demand instances. Managed services ensure extensive scaling, although occasionally, resource allocation may lag. It supports enterprises and vast user bases, processing substantial data volumes. Despite minor performance issues, it suits data analytics and customization for specific cases, enabling seamless scaling for diverse organizational requirements.

Users find Amazon EMR stable, with high availability and reliability. Some recommend monitoring configurations as data changes, but issues are minimal. Users rate its steadiness highly, noting its support from availability zones, failover capabilities, and fault tolerance. Regular updates, monitoring, logging, and disaster recovery contribute positively. Despite occasional minor issues, users express confidence in its performance, suggesting it meets expectations in most scenarios. Stability ratings are generally eight to nine out of ten.