

Amazon EMR and SAP Business Data Cloud are major competitors in the big data and analytics space. Amazon EMR holds the upper hand for handling large data volumes efficiently.
Features: Amazon EMR is noted for its exceptional integration with Big Data tools, automatic scaling, and managed services like Spark and Hive. Its capacity for real-time data processing and cost efficiency is enhanced when migrated to EKS. SAP Business Data Cloud distinguishes itself through analytic application design, user-friendliness, and seamless integration with SAP's ecosystem, making it a favorite for predictive analytics and collaborative features.
Room for Improvement: Amazon EMR can improve by expanding its visualization tools, enhancing AI/ML functionalities, and better integration with services such as Glue and DynamoDB. Customization and cost management pose challenges. SAP Business Data Cloud needs more integration with non-SAP tools, enhanced visualization, and predictive capabilities, along with real-time reporting improvements and additional connector support.
Ease of Deployment and Customer Service: Amazon EMR's deployment is straightforward in public cloud environments, with responsive but occasionally inconsistent technical support. SAP Business Data Cloud supports various deployment models, offering responsive support, but it needs stronger multi-cloud integrations. While Amazon EMR emphasizes integration within AWS, SAP Business Data Cloud focuses on broad SAP product integration.
Pricing and ROI: Amazon EMR offers a usage-based model focused on resource consumption, which can be cost-effective but may lead to unexpectedly high costs if unmonitored. Its ROI is often high for transitions from on-premise systems. SAP Business Data Cloud is viewed as expensive due to advanced functionalities and licensing, yet it provides favorable ROI against on-premise systems due to SAP integration benefits. Both products emphasize value-based usage, with Amazon often seen as more cost-effective for Big Data processing.
We have saved a lot on the number of employees, and implementation time for the projects has reduced significantly since we started using the standard features of SAP Business Data Cloud.
Once the content is available, then it is a faster go-live with lesser cost in implementation, and that would give an ROI.
There is a return on investment with SAP Business Data Cloud, as it saves money because it performs results quickly and easily, facilitating integrations and speeding up operations compared to other analytics tools, thereby saving time and money.
They help with billing, cost determination, IAM properties, security compliance, and deployment and migration activities.
We get all call support, screen sharing support, and immediate support, so there are no problems.
I would rate the technical support from Amazon as ten out of ten.
The technical support is a very well-organized service, with a lot of tools for me as a consultant and for the end user on how to contact SAP support and get issues solved.
For example, when I provide a set of instructions, they often simply ask me to implement those steps without checking whether they are applicable.
In SAP's policy, for the first couple of years, the product team is also part of the support team.
Scalability can be provisioned using the auto-scaling feature, EC2 instances, on-demand instances, and storage locations like block storage, S3, or file storage.
SAP Analytics Cloud can be used by a small company, and it can be used by a large corporate.
Since SAP has consolidated everything on one platform, there is ample room to expand as much as needed.
There are no limitations in terms of scale, so it fits both SMB customers and enterprise customers.
Regular updates, patch installations, monitoring, logging, alerting, and disaster recovery activities are crucial for maintaining stability.
You have a chance to test it on your test tenant in small increments, so it should not break your productive reports and productive environment.
Other than during these quarterly release periods, the availability is excellent.
In a typical quarter, the availability has been over 99%; in a few cases, it dropped to around 98.5%.
The cost factor differs significantly. When you run Spark application on EKS, you run at the pod level, so you can control the compute cost. But in Amazon EMR, when you have to run one application, you have to launch the entire EC2.
There is room for improvement with respect to retries, handling the volume of data on S3 buckets, cluster provisioning, scaling, termination, security, and integration between services like S3, Glue, Lake Formation, and DynamoDB.
I have thoughts on what would be great to see in the product, such as AI/ML features or additional options.
On the other hand, it is perfectly fitting to the SAP environment, with seamless integration to all SAP modules, not only ERP but also SuccessFactors and other tools from the SAP family.
If SAP can come up with innovative options to reduce licensing costs, many customers would incline toward SAP Business Data Cloud.
If I compare the cost with SAP competitors, I find that when creating an enterprise data lake, if I don't use SAP Business Data Cloud and make it directly in the hyperscalers, it is pretty much cheaper than doing the same in SAP Business Data Cloud.
Costs are involved based on cluster resources, data volumes, EC2 instances, instance sizes, Kubernetes, Docker services, storage, and data transfers.
I would rate the price for Amazon EMR, where one is high and ten is low, as a good one.
If I compare the cost with SAP competitors, I find that when creating an enterprise data lake, if I don't use SAP Business Data Cloud and make it directly in the hyperscalers, it is pretty much cheaper than doing the same in SAP Business Data Cloud.
Frankly, pricing, setup cost, and licensing seem a bit high compared to other hyperscalers.
The pricing for SAP Business Data Cloud is higher compared to alternatives.
Amazon EMR helps in scalability, real-time and batch processing of data, handling efficient data sources, and managing data lakes, data stores, and data marts on file systems and in S3 buckets.
Amazon EMR provides out-of-the-box functionality because we can deploy and get Spark functionality over Hadoop.
The features at Amazon EMR that I have found most valuable are fully customizable functions.
For SuccessFactors and S/4HANA Cloud, there are pre-built reports available which are commonly used by customers.
SAP Business Data Cloud has positively impacted my organization by federating SAP data, which is now available for all to use.
The main standout feature is BDC Connect, as it is very useful for sharing data without replicating to third-party tools such as Enterprise Databricks, Snowflake or even in the near future, Google BigQuery as well as Microsoft Fabric.
| Product | Mindshare (%) |
|---|---|
| SAP Business Data Cloud | 2.8% |
| Amazon EMR | 3.8% |
| Other | 93.4% |
| Company Size | Count |
|---|---|
| Small Business | 6 |
| Midsize Enterprise | 5 |
| Large Enterprise | 12 |
| Company Size | Count |
|---|---|
| Small Business | 28 |
| Midsize Enterprise | 19 |
| Large Enterprise | 51 |
Amazon EMR simplifies big data processing by offering integration with popular tools. It's scalable and cost-efficient, enabling fast processing while managing infrastructure effortlessly. It's designed for users aiming to streamline data workflows and leverage its batch processing capabilities effectively.
Amazon EMR is a managed service that provides robust features for big data processing. It integrates seamlessly with S3, EC2, Hive, and Spark to facilitate sophisticated data transformation tasks and infrastructure management. It allows organizations to run data lakes, Spark, and Hadoop clusters effortlessly, offering flexibility with on-demand execution and extensive scalability. The platform is valued for its strong processing speed and comprehensive security features, making it ideal for complex data engineering projects. It supports both batch processing and real-time workflows, designed to eliminate hardware management while maintaining cost efficiency and stability.
What are the key features of Amazon EMR?Amazon EMR is implemented by industries such as healthcare and tech processing for complex data tasks like building data lakes or financial data processing. It supports AI-driven analytics and data engineering projects, integrating with SageMaker for predictions and maintaining workflows in public health applications, allowing professionals in different fields to manage data pipelines, resource utilization, and job execution efficiently.
SAP Business Data Cloud provides cloud-based predictive analysis, robust visualization, and integrated planning capabilities with seamless SAP integration. It enhances analytics and reporting efficiency with machine learning and AI features.
SAP Business Data Cloud stands out with its user-friendly application design, leveraging TypeScript scripting for flexibility. It enables easy data integration, customizable dashboards, and collaborative planning. Renowned for its seamless connectivity and comprehensive business intelligence offerings, it is designed to support real-time analytics and planning across both on-prem and cloud environments. Improvements are anticipated in visualization features, connectivity, and third-party system integration, with calls for more customizable chart options and real-time reporting capabilities.
What are the most important features of SAP Business Data Cloud?SAP Business Data Cloud serves industries by powering cloud-based reporting, analytics, financial planning, and executive dashboards. Companies utilize it to integrate SAP and non-SAP data sources for insights and forecasts. It is applied in constructing dashboards, boardroom presentations, budgeting, and predictive analytics, supporting versatile use cases across multiple sectors.
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