

SAP S4HANA on AWS and Amazon Bedrock are competitors in cloud-based enterprise solutions. SAP S4HANA on AWS seems to have the upper hand with its comprehensive ERP functionalities, while Amazon Bedrock excels in AI capabilities and flexible model integration, appealing to AI-driven enterprises.
Features: SAP S4HANA on AWS offers comprehensive modules covering finance, manufacturing, and analytics, allowing effective management of complex ERP functions. Its seamless integration with AWS infrastructure reduces hardware dependency, enhancing cost-efficiency. Amazon Bedrock provides customizable AI models and easy experimentation with Generative AI, making it ideal for companies seeking AI-driven insights. The integration with pre-trained models is a significant advantage for businesses focused on AI applications.
Room for Improvement: SAP S4HANA on AWS needs a simplified interface and improved licensing model. Users have raised concerns about technical support, hardware costs, and integrating with newer technologies. There's also a call for more data centers and enhanced training resources. For Amazon Bedrock, improving cost transparency and expanding AI capabilities are key areas. Better documentation and additional integration points would refine user experience, alongside addressing unexpected costs.
Ease of Deployment and Customer Service: SAP S4HANA on AWS offers flexibility with public, private, and hybrid cloud deployment options, though its technical support needs improvement due to reported response delays. Amazon Bedrock focuses on public cloud deployment, known for straightforward implementation and generally positive technical support with efficient response times, yet a more extensive knowledge base could benefit the growing community.
Pricing and ROI: SAP S4HANA on AWS is viewed as costly due to high hardware expenses and complex licensing, but it yields a strong return on investment with increased efficiency over time. Amazon Bedrock is competitively priced for its features, though concerns about unexpected charges persist. Its cost model is appealing for AI experimentation compared to other offerings, with users noting its fair pricing for available capabilities.
Amazon Bedrock enabled the use of huge models and the democratization of their use at comparatively low cost, if we host these models in the company.
On a very good implementation, usually, if the scale of the business is large, the implementation can give a payback within six, seven, or eight months of implementation.
Although our investment was higher compared to the previous ERP system, we are able to derive ROI from SAP S4HANA on AWS.
We are experiencing the fastest time ever to get things done with AI integrating into our work, regardless of where we are.
So, you always have to bridge the gap by presenting scenarios, getting recommendations, and testing or validating those assumptions.
My experience with the technical support has been very good because they resolved my billing issue within a day.
They have a support model available, with first-level support handling initial issues when I integrate the system.
We received the right support during our implementation and continue to benefit from it.
It is scalable on a truly global basis.
Amazon Bedrock is quite highly scalable, but there are some limitations they impose on the accounts, which could be an area for improvement.
It scales well with AWS Lambda, AWS Transcribe, and Polly.
AWS has been running probably 96% of Fortune 500 companies across the globe, so scalability is not an issue.
The product is versatile and can manage complexity beyond expectations.
The stability of Amazon Bedrock is good as I have not faced any issues.
As a finance controller, we have seen improvements in finance deliverables, SLAs in payables, and reconciliation timelines.
In AgenTek AI business, the only foundation models we can rely on for scaling now are the Cloud 3.5 models like Haiku and SONNET, designed for low latency and complex AI business use cases.
For companies in general, the main pain point or main issue related to Amazon Bedrock is security because they are not confident that all information is hidden by this kind of architecture.
If AWS provided methods, like five or six prompts that yield specific results, it would ease development.
The interface and interaction with the technical team require intensive training.
SAP introduced flexible workflows, which are even better if I want customized workflows for my documentation within the procurement domain.
Having these integrations as a single source rather than working in silos would be beneficial for customers.
Our cost is incredibly low, operating for a few hundred dollars a month in production.
One customer paid around $100 to $200 per month, which was significant given their overall infrastructure costs.
The pricing and licensing of Amazon Bedrock are quite flexible.
SAP is not cheap, with many hidden costs encountered during implementation.
The initial setup required a higher investment, but the return on investment has justified the cost.
It has improved operational costs and efficiency significantly, saving money and enhancing the quality of operations.
The valuable features that have helped in leveraging generative AI for operational efficiency improvements include customization capabilities, various types of models suitable for specific use cases, and the integration of knowledge bases.
The ability to make changes in the foundational model is valuable since different customers have specific needs, allowing customization.
The costing and personnel planning integration are among the strongest areas of this solution.
From the finance side, we have enhanced our internal controls and reduced the timeline for closing the month from a year to just two days.
It manages complexity in various industries such as banking, manufacturing, and trading.
| Product | Market Share (%) |
|---|---|
| Amazon Bedrock | 1.8% |
| SAP S4HANA on AWS | 2.6% |
| Other | 95.6% |


| Company Size | Count |
|---|---|
| Small Business | 8 |
| Midsize Enterprise | 1 |
| Large Enterprise | 7 |
| Company Size | Count |
|---|---|
| Small Business | 19 |
| Midsize Enterprise | 8 |
| Large Enterprise | 15 |
Amazon Bedrock offers comprehensive model customization and integration with AWS services, making AI development more flexible for users. It streamlines content generation and model fine-tuning with a focus on security and cost efficiency.
Amazon Bedrock is engineered to provide a seamless AI integration experience with a strong emphasis on security and user-friendliness. It simplifies AI development by offering foundational models and managed scaling, enhancing both trust and operational efficiency. With its versatile model customization and ease of integration, Bedrock reduces the need for extensive infrastructure management. It supports businesses in deploying pre-trained models, performing generative AI tasks, and improving analytics through AI technologies such as chatbots, sentiment analysis, and data formatting.
What are the key features of Amazon Bedrock?Amazon Bedrock is applied across industries for implementing AI-driven solutions like enhancing customer service with chatbots and improving data analysis with sentiment analysis tools. Businesses create knowledge bases, automate business processes, and utilize pre-trained models for tasks such as invoice processing and customer call analysis. Its integration with large language models assists in text and image generation, offering diverse AI capabilities adaptable to industry needs.
SAP customers of all sizes can fully realize all the benefits of the SAP S/4HANA, on-premise edition on the AWS Cloud. With SAP S/4HANA, on-premise edition on the AWS Cloud you can:
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