A comparative study of cloud platforms for SAP system deployments

 Corresponding author: Naveen Karuturi Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution License 4.0. A comparative study of cloud platforms for SAP system deployments Naveen Karuturi * University of South Alabama, USA. World Journal of Advanced Research and Reviews, 2025, 26(02), 115-126 Publication history: Received on 21 March 2025; revised on 27 April 2025; accepted on 30 April 2025 Article DOI: https://doi.org/10.30574/wjarr.2025.26.2.1548 Abstract This technical article provides a detailed comparison of leading cloud platforms for SAP system deployments, examining how each provider addresses the unique requirements of enterprise resource planning environments. By evaluating Amazon Web Services, Microsoft Azure, Google Cloud Platform, IBM Cloud, and Oracle Cloud Infrastructure across key dimensions including performance capabilities, certification coverage, pricing models, migration tools, security frameworks, and specialized services, the article offers decision-makers essential insights for platform selection. The evaluation encompasses both technical considerations such as SAPS ratings and performance consistency, as well as strategic factors including hybrid architecture support, ecosystem integration, and organizational alignment. Through systematic assessment of each platform's distinctive strengths and limitations, organizations can identify optimal deployment environments that align with their specific SAP implementation requirements, operational priorities, and long-term business objectives. Keywords: Agility; Cloud Platform; Ecosystem Integration; Enterprise Resource Planning; Sap Deployment 1. Introduction Enterprise Resource Planning (ERP) systems form the backbone of modern business operations, with SAP standing as one of the most widely adopted solutions globally. SAP's significant market presence has grown to serve more than 440,000 customers across 180 countries, with approximately 87% of Forbes Global 2000 companies utilizing SAP solutions [1]. The company's robust portfolio powers countless critical business functions from finance to manufacturing, driving operational efficiency for organizations of all sizes. As organizations increasingly migrate their SAP workloads to the cloud, selecting the optimal platform has become a critical decision with far-reaching implications for performance, scalability, cost efficiency, and long-term business agility. This migration trend reflects broader digital transformation initiatives, with cloud adoption for mission-critical applications growing at impressive rates. Organizations implementing cloud-based SAP deployments report an average of 20-30% reduction in infrastructure costs and 40% improvement in deployment speed compared to traditional onpremises implementations [2]. The cloud migration journey typically spans 12-18 months for large enterprises, with companies achieving positive return on investment within an average timeframe of 18-24 months post-migration. This technical analysis examines the leading cloud platforms supporting SAP deployments, providing decision-makers with comprehensive insights into their respective strengths, limitations, and specialized offerings. Each platform offers distinct advantages: hyperscaler solutions provide vast scalability with some supporting up to 24TB HANA instances, while specialized providers may offer tailored optimization capabilities that improve performance by 15-20% for specific SAP modules [2]. Performance benchmarks from real-world implementations show significant variations in transaction processing times, with differences of up to 35% between optimally and sub-optimally configured environments. World Journal of Advanced Research and Reviews, 2025, 26(02), 115-126 116 By understanding the nuanced differences between these platforms, organizations can make informed choices aligned with their specific SAP implementation requirements and broader business objectives. Strategic platform selection directly impacts operational KPIs, with properly configured cloud deployments demonstrating 99.95% or higher system availability compared to the industry average of 99.5% for traditional deployments [2]. Furthermore, scalability considerations are paramount, as SAP workloads typically grow by 25-30% annually in data-intensive sectors such as manufacturing and retail, requiring flexible infrastructure that can accommodate this expansion without service disruption. 2. Key Cloud Platforms for SAP Deployments 2.1. Amazon Web Services (AWS) AWS offers extensive support for SAP workloads through its purpose-built infrastructure and specialized services. The platform provides SAP-certified instances optimized for various workload profiles, including memory-intensive applications like SAP HANA. According to comprehensive cloud service provider analysis, AWS maintains a substantial portion of enterprise SAP deployments, with approximately 37% of migrated SAP workloads residing on their infrastructure [3]. Performance benchmarks demonstrate that properly configured AWS environments for SAP applications can achieve response time improvements of up to 41% compared to traditional on-premises deployments. AWS's global infrastructure spans multiple geographic regions with numerous availability zones, providing the foundation for high-availability architectures essential for mission-critical SAP systems. Studies of enterprise cloud migrations indicate that organizations leveraging AWS for SAP deployments experience an average of 65% improvement in infrastructure deployment speed and 71% reduction in provisioning time [4]. This expansive infrastructure footprint enables robust disaster recovery capabilities, with documented recovery point objectives (RPOs) as low as 5 minutes for synchronously replicated SAP environments utilizing cross-region architectures. AWS's SAP offerings are particularly notable for their flexibility, allowing customers to choose between various deployment models including AWS-managed services or self-managed infrastructure. Research indicates that this flexibility translates to measurable financial benefits, with organizations implementing SAP on AWS reporting average operational cost reductions of 26% compared to previous infrastructure approaches [3]. The platform's wellestablished migration methodologies provide standardized approaches for transitions, with documented migration success rates of 97.3% for implementations following AWS's recommended practices. Quantitative analysis of enterprise migrations reveals that organizations utilizing these methodologies completed their transitions approximately 2.3 times faster than those employing custom migration approaches. 2.2. Microsoft Azure Microsoft Azure presents unique advantages for organizations with existing Microsoft technology investments, offering tight integration between SAP applications and Microsoft's enterprise software ecosystem. Cloud adoption research indicates that Azure hosts approximately 32% of cloud-based SAP workloads, with particularly strong representation among organizations already invested in Microsoft's business application portfolio [3]. Technical implementation studies show that Azure-hosted SAP environments integrated with Microsoft's broader ecosystem can reduce crossapplication data latency by up to 54% compared to siloed architectural approaches. Azure's strategic partnership with SAP has produced numerous technical integrations that streamline implementation and management processes. Performance analysis demonstrates that these integrations contribute to implementation timelines that average 29% shorter than comparable non-integrated deployments [4]. The extended integration capabilities enable enhanced operational visibility, with integrated monitoring solutions detecting potential system issues up to 73% faster than stand-alone monitoring approaches. This integration ecosystem serves a substantial portion of enterprise SAP customers, with approximately 68% of organizations running SAP on Azure also leveraging additional Microsoft services. The platform's approach emphasizes operational cohesion between SAP environments and Microsoft's data platform, analytics, and AI services. Organizations implementing these integrated analytics capabilities report achieving insight generation timelines averaging 64% faster than with traditional business intelligence approaches [3]. This integration can be particularly valuable for organizations looking to derive additional business intelligence from their SAP data stores, with case study analysis demonstrating that integrated environments produce approximately 3.7 times more actionable business insights than non-integrated architectural approaches. World Journal of Advanced Research and Reviews, 2025, 26(02), 115-126 117 2.3. Google Cloud Platform (GCP) Google Cloud has rapidly evolved its SAP capabilities, offering innovative solutions that leverage Google's strengths in networking, analytics, and artificial intelligence. Market analysis indicates that GCP hosts approximately 16% of cloudbased SAP workloads, with adoption rates increasing by approximately 42% annually since 2019 [3]. Performance studies demonstrate that GCP's networking architecture delivers consistent performance for SAP applications, with measured latency variations under 5% even during peak utilization periods. Google's Live Migration technology for maintenance without downtime has demonstrated particular value for SAP environments. Empirical studies show that this capability eliminates an average of 23.8 hours of planned downtime annually for SAP production systems [4]. Performance analysis of GCP's network infrastructure shows consistent throughput capabilities, supporting efficient data replication for SAP landscapes with documented inter-region transfer rates sufficient for maintaining RPOs under 10 minutes for databases up to 8TB in size. GCP's dedicated hardware solutions for SAP HANA workloads offer certified configurations supporting enterprise-scale implementations, with documented performance consistency ratings exceeding 97% across measurement periods [3]. Advanced analytics integration capabilities provide enterprises with substantive business intelligence advantages, with measured query performance improvements averaging 58% for complex analytical workloads compared to traditional data warehousing approaches. GCP's approach to SAP deployments emphasizes performance predictability and operational reliability, with 94.6% of surveyed customers indicating that actual performance metrics aligned with premigration projections. 2.4. IBM Cloud IBM Cloud offers differentiated value for SAP deployments through its deep enterprise experience and hybrid cloud capabilities. Market analyses position IBM Cloud with approximately 9% of cloud-based SAP workloads, with particularly strong representation in highly regulated industries including financial services, healthcare, and public sector [3]. Performance evaluations demonstrate that IBM's specialized hardware options for SAP HANA deliver substantial performance advantages for certain workloads, with analytical processing benchmarks showing improvements averaging 37% for complex query workloads. IBM's extensive consulting expertise for complex SAP transformations builds upon decades of implementation experience. Migration studies indicate that organizations leveraging this expertise achieve on-time implementation rates approximately 34% higher than industry averages [4]. Technical analysis shows that specialized hardware configurations deliver significant performance advantages for memory-intensive operations, which translates to measurable improvements in business process execution times averaging 28% for transactions with intensive database components. The platform's integrated data protection and disaster recovery services have demonstrated robust capabilities for maintaining business continuity. Technical evaluations document recovery time objectives (RTOs) averaging 76% faster than comparable solutions when implementing IBM's recommended high-availability architectures [3]. IBM's strong heritage in mission-critical enterprise systems provides notable advantages, with reliability measurements showing approximately 99.986% availability for properly architected SAP landscapes. This offering is particularly wellsuited for organizations with complex regulatory requirements or those pursuing a hybrid deployment model that spans on-premises and cloud environments, with approximately 65% of IBM's SAP customers implementing hybrid architectural approaches. 2.5. Oracle Cloud Infrastructure (OCI) As both a cloud provider and a database vendor competing with SAP HANA, Oracle offers unique capabilities for certain SAP deployments. Market analysis indicates that OCI hosts approximately 8% of cloud-based SAP workloads, with particularly strong representation among organizations running SAP applications on Oracle databases [3]. Performance testing demonstrates that OCI-hosted Oracle databases supporting SAP applications deliver query response times averaging 27% faster than the same database configurations on alternative platforms. OCI's compute instances with high memory configurations support enterprise-scale SAP implementations with performance consistency ratings exceeding 95% during extended measurement periods [4]. The platform's predictable pricing model with consistent performance has financial implications for SAP operations, with total cost of ownership analyses showing potential savings averaging 23.5% over five-year periods compared to equivalent configurations on alternative platforms for specific workload profiles. World Journal of Advanced Research and Reviews, 2025, 26(02), 115-126 118 Oracle's database migration tools and expertise provide advantages for certain migration scenarios, with documented migration success rates of 99.2% for SAP environments transitioning from on-premises Oracle databases to OCI [3]. OCI may present compelling advantages for organizations running SAP applications on Oracle databases, providing a streamlined path to cloud migration while maintaining database consistency. Technical evaluations indicate that these organizations can achieve migration completion with approximately 47% less technical risk compared to migrations involving database platform changes. Table 1 Cloud Provider Market Share for SAP Workloads [3, 4] Cloud Provider Market Share (%) Performance Improvement (%) Migration Success Rate (%) Operational Cost Reduction (%) AWS 37 41 97.3 26 Azure 32 54 94.0 29 Google Cloud 16 58 94.6 24 IBM Cloud 9 37 92.0 28 Oracle Cloud 8 27 99.2 23.5 3. Key Evaluation Criteria 3.1. SAP Certification and Support All major cloud providers maintain SAP certifications for their infrastructure offerings, but the scope and depth of these certifications vary significantly across platforms. According to cloud evaluation framework analysis, certification coverage ranges from 67% to 93% of available SAP application scenarios depending on the provider, with AWS and Azure demonstrating the most comprehensive certification portfolios [5]. This variation becomes particularly important when considering that properly certified environments show an average of 42% fewer compatibility issues during implementation phases. Google Cloud and IBM have focused their certification efforts on high-value workloads, particularly SAP S/4HANA, with targeted optimization efforts delivering measurable performance improvements specifically for these next-generation applications. The evaluation of certification quality should extend beyond simple availability to include detailed assessment of certification testing methodologies. Research indicates that certifications encompassing real-world workload simulations provide approximately 30% more reliable performance predictions than those based on standardized benchmarks alone [6]. Organizations should examine not just the presence of certification, but also the recency of certification testing and the specific scenarios covered. Cloud evaluation studies demonstrate that certifications incorporating stress testing under variable load conditions provide substantially more predictive value for production performance, with consistency measurements varying by up to 25% between providers using different certification methodologies. This becomes especially important for specialized SAP modules or custom applications dependent on specific infrastructure characteristics, where infrastructure-application compatibility can significantly impact overall system stability. 3.2. Performance Benchmarks Performance benchmarks reveal significant differences in how platforms handle SAP workloads, particularly for dataintensive operations. Comparative framework analysis documents substantial variations in processing capacity across providers, with SAPS ratings providing standardized comparison metrics [5]. AWS instances demonstrate SAPS ratings exceeding 250,000 for their largest SAP-certified configurations, enabling support for large-scale enterprise workloads. Azure configurations achieve SAPS ratings surpassing 300,000, positioning them at the higher end of the performance spectrum for memory-intensive applications. GCP instances provide SAPS ratings above 220,000, offering sufficient capacity for most enterprise SAP implementations while emphasizing cost-performance optimization. The performance evaluation extends beyond computational capacity to encompass specific SAP workload characteristics. Benchmark studies examining data load operations for SAP HANA implementations identify variations of up to 35% in throughput rates across platforms under standardized test conditions [6]. For analytical processing scenarios typified by SAP BW, performance measurements reveal query execution time differences averaging 28%, with platform-specific optimizations demonstrating substantial impact on complex query performance. Industry World Journal of Advanced Research and Reviews, 2025, 26(02), 115-126 119 benchmarking initiatives have documented that IBM Power architectures deliver exceptional performance for certain SAP workloads, while Oracle Cloud Infrastructure provides particularly consistent performance for database-intensive operations. It's worth noting that raw performance metrics tell only part of the story. Performance consistency—how predictably a platform maintains performance levels under varying conditions—can be equally important for missioncritical SAP workloads, with evaluation frameworks identifying consistency variations of 5-18% across major providers during peak load conditions. 3.3. Pricing Models and TCO Cloud platforms utilize different pricing approaches for SAP deployments, creating significant total cost of ownership variations based on specific implementation characteristics. Evaluation framework analysis indicates that effective discount structures can reduce nominal costs by 25-60% depending on commitment levels and resource consumption patterns [5]. AWS emphasizes flexibility with on-demand, reserved, and Savings Plans options, with maximum discount levels approaching 72% for long-term commitments. Azure provides reserved instances and licensing benefits for existing Microsoft customers, creating potential cost advantages through license mobility across deployment models. GCP features usage-based discount structures that scale with consumption levels, delivering incremental savings as workload scale increases without requiring upfront commitments. Beyond the base infrastructure costs, comprehensive evaluation methodologies highlight the importance of considering multiple cost components. Cloud monitoring research demonstrates that ancillary costs including data transfer, storage, and specialized services typically account for 15-40% of total expenditure for distributed SAP landscapes [6]. Database licensing implications vary substantially across platforms, with significant impact on total costs for database-intensive applications like SAP. Data transfer costs between regions and services can constitute a substantial portion of operational expenses, particularly for globally distributed implementations requiring frequent cross-region communication. Backup and disaster recovery pricing models demonstrate variations of 10-45% across providers for equivalent protection levels, with significant implications for overall operational expenditure. Support costs and service level agreements introduce further variability, with premium support options increasing base costs by 12-25% while providing enhanced response times and access to specialized expertise. 3.4. Migration Tools and Services Cloud providers have developed specialized tools to facilitate SAP migrations, with significant variations in capability maturity and automation levels. Evaluation framework assessments indicate that migration acceleration programs can reduce project timelines by 25-45% compared to standard migration methodologies [5]. AWS offerings provide structured approaches combining technical tools with implementation expertise, supporting complex migration scenarios with demonstrated success rates. Azure solutions deliver automation capabilities for deployment and configuration management, reducing manual effort requirements while improving consistency. Google Cloud provides migration factory approaches emphasizing repeatable processes and quality control mechanisms, particularly valuable for organizations with multiple migration phases. The sophistication of migration tooling varies substantially across providers, with direct implications for project outcomes. Comparative analysis indicates that automated transformation approaches can reduce migration-related code customization efforts by 30-60% compared to manual methods [6]. IBM migration services emphasize technical expertise combined with specialized tooling, delivering particular value for complex transformations requiring extensive business process knowledge. Oracle solutions facilitate migrations for organizations with existing Oracle database investments, minimizing database transition complexity while streamlining overall migration processes. The maturity and capabilities of these migration tools can significantly impact project timelines, risk profiles, and total migration costs, with research indicating that organizations leveraging provider-specific migration tooling experience substantially higher success rates for complex migration scenarios. 3.5. Security and Compliance All major providers offer robust security capabilities, but with different emphases that align with varying compliance requirements. Evaluation framework analysis indicates that security implementation approaches vary significantly, with different providers demonstrating distinctive strengths for specific security dimensions [5]. AWS provides extensive policy management capabilities and certification coverage, supporting implementations in highly regulated environments with specific compliance requirements. Azure integrates identity management and threat protection capabilities, leveraging Microsoft's broader security ecosystem to deliver comprehensive protection. GCP emphasizes architectural security principles and transparent security models, with strong controls for infrastructure-level protection against common threat vectors. World Journal of Advanced Research and Reviews, 2025, 26(02), 115-126 120 Security capabilities should be evaluated within the context of specific organizational requirements, with particular attention to compliance needs for regulated industries. Monitoring and evaluation research demonstrates that cloud providers achieve compliance readiness scores varying by 10-30% across different regulatory frameworks [6]. IBM delivers strong capabilities for regulated industries with specific compliance requirements, building upon extensive experience in these sectors. OCI provides isolation-focused security controls with strong emphasis on network-level protections, delivering advantages for security models prioritizing network segmentation. Organizations should assess these capabilities against their specific security requirements, particularly for industries with stringent regulatory obligations, with framework analysis demonstrating that alignment between platform security architecture and compliance requirements can reduce compliance management efforts by 20-35% compared to implementations requiring extensive customization to meet regulatory standards. Table 2 Comparative Analysis of Cloud Platform Capabilities for SAP Deployments [5, 6] Cloud Provider Certification Coverage (%) Performance Consistency Variation (%) Maximum Discount Level (%) Migration Timeline Reduction (%) AWS 93 5 72 45 Azure 89 8 65 40 Google Cloud 78 12 57 35 IBM Cloud 75 15 50 38 Oracle Cloud 67 18 48 30 4. Strategic Considerations for Platform Selection 4.1. Hybrid and Multi-Cloud Capabilities Many enterprises maintain hybrid SAP environments spanning on-premises and cloud deployments, or distribute workloads across multiple cloud providers. Research analyzing cloud service provider capabilities indicates that approximately 68% of enterprises implementing SAP solutions maintain some form of hybrid architecture, with technical requirements and compliance considerations being primary drivers of this approach [7]. Comparative analysis shows that latency between on-premises and cloud components remains a significant concern, with average response time differences of 55-85 milliseconds potentially impacting performance-sensitive SAP modules. AWS Outposts brings AWS infrastructure to on-premises environments, enabling organizations to maintain consistent infrastructure while addressing data residency requirements. Performance analysis indicates that this approach can reduce cross-environment communication latency by up to 60% compared to traditional hybrid architectures [7]. Azure Arc enables consistent management across hybrid environments, providing unified policy implementation and centralized monitoring capabilities that have been shown to reduce management complexity by approximately 40% according to comparative cloud service evaluations. This management consistency is particularly valuable for organizations with limited specialized cloud expertise, who report spending an average of 12-15 hours per week on environment management tasks. Google Anthos provides a unified management plane for multi-cloud deployments, with implementation studies showing that this approach can reduce operational complexity by approximately 35% for organizations maintaining components across multiple environments [8]. IBM Cloud Satellite extends IBM Cloud capabilities to diverse environments, addressing data sovereignty requirements while maintaining centralized management capabilities. Comparative research indicates that approximately 53% of organizations cite compliance requirements as a primary motivation for maintaining hybrid architectures. Oracle Dedicated Region Cloud@Customer delivers OCI services onpremises, providing particularly strong performance characteristics with reported latency metrics within 5-10% of dedicated on-premises infrastructure. These capabilities become particularly relevant for phased SAP migrations or when maintaining certain components on-premises due to regulatory or latency requirements. Cloud service provider analysis indicates that approximately 45% of enterprises maintain hybrid SAP architectures for at least 24 months during migration initiatives [7]. Comparative evaluations reveal that organizations implementing structured migration approaches achieve World Journal of Advanced Research and Reviews, 2025, 26(02), 115-126 121 approximately 35% higher success rates for complex transitions, with extended hybrid operation serving as an effective risk mitigation strategy for business-critical systems. 4.2. Ecosystem Integration The value of cloud-based SAP deployments often extends beyond the core ERP functionality through integration with other services. Cloud service provider analysis indicates that integration capabilities represent a significant decision factor, with approximately 62% of organizations rating ecosystem integration among their top five selection criteria [7]. Comparative analysis of integration approaches shows that organizations with well-integrated environments report approximately 30% higher satisfaction with their overall cloud implementation outcomes. AWS provides extensive integration with its analytics, machine learning, and IoT services. Studies of integration complexity indicate that AWS's unified identity and security model reduces implementation effort by approximately 2530% compared to cross-platform integration approaches [8]. Organizations implementing integrated analytics report data preparation time reductions averaging 40%, with particular benefits for complex data transformation scenarios. Azure offers tight coupling with Microsoft's business application ecosystem, with comparative analyses indicating that organizations with existing Microsoft investments achieve implementation timelines approximately 20% shorter than those without established ecosystem familiarity. GCP excels in data analytics and AI integration possibilities, with comparative research highlighting significant performance advantages for analytical workloads. Organizations implementing these integrations report processing time improvements averaging 30-35% for complex analytical queries spanning multiple data sources [7]. IBM delivers strong integration with its business process optimization solutions, with particular strengths in document processing and workflow automation. Integration studies indicate efficiency improvements of approximately 25% for processes spanning SAP and complementary applications. OCI provides seamless connectivity with Oracle's application portfolio, with technical assessments indicating approximately 45% reduced integration complexity for environments combining SAP and Oracle applications. These integration possibilities should be evaluated against the organization's broader technology strategy and existing investments. Research examining cloud provider selection criteria indicates that approximately 57% of organizations consider ecosystem alignment a critical factor, with particular emphasis on analytics capabilities (cited by 64% of respondents) and machine learning integration (cited by 48% of respondents) [8]. Comparative provider analysis demonstrates that pre-built integrations can reduce implementation timelines by 20-60% depending on complexity, representing significant value for organizations with limited development resources. 4.3. Specialized SAP Services Cloud providers have developed specialized services addressing specific SAP scenarios. Comparative analysis indicates that these purpose-built offerings deliver significant advantages compared to generic services, with research showing that organizations leveraging specialized capabilities achieve approximately 30% higher operational efficiency for routine management tasks [7]. These specialized services demonstrate particular value for technically complex scenarios, with simplified approaches reducing configuration errors by an estimated 40-60% compared to manual implementation processes. Database services optimized for SAP workloads deliver measurable performance and management advantages. Comparative evaluation of database performance indicates throughput variations of 15-40% between optimized and general-purpose configurations under equivalent test conditions [8]. Administrative efficiency analyses show that purpose-built services reduce routine database management efforts by approximately 25-30%, with particularly strong advantages for backup and recovery operations. Provider-specific database optimizations demonstrate considerable value for performance-sensitive operations, with response time improvements of 10-25% for common transaction patterns. Automation capabilities tailored to SAP deployment scenarios drive significant operational advantages. Implementation studies indicate that automated deployment approaches reduce implementation timelines by approximately 50-70% compared to manual processes, with consistency improvements exceeding 80% across repeated deployments [7]. Organizations implementing comprehensive automation report staffing requirement reductions of approximately 0.51.5 full-time equivalents for environment management, representing significant operational cost savings. Comparative analysis of provider capabilities shows substantial variation in automation maturity, with differences of 35-45% in coverage for common management tasks between leading and trailing providers. World Journal of Advanced Research and Reviews, 2025, 26(02), 115-126 122 Analytics integration capabilities demonstrate substantial business value through enhanced decision support. Comparative analysis of analytics performance shows query execution time variations of 20-50% between platforms for complex analytical scenarios involving SAP data [8]. Organizations implementing integrated analytics report insight generation timeline improvements averaging 30%, with particular benefits for scenarios requiring near-real-time analysis of operational data. These specialized analytics capabilities contribute measurably to business outcomes, with approximately 55% of organizations reporting improved decision quality as a direct result of enhanced analytical capabilities applied to SAP data. Disaster recovery capabilities tailored for SAP environments provide both technical and operational advantages. Comparative evaluation of recovery performance shows significant variation between providers, with recovery time differences of 15-60% for equivalent configurations [7]. Organizations implementing specialized disaster recovery approaches report confidence level improvements averaging 25% regarding their ability to meet recovery time objectives during actual failure events. These specialized services can dramatically simplify operations and extend the capabilities of SAP implementations, with research indicating that organizations leveraging purpose-built SAP services achieve overall operational cost reductions averaging 15-25% compared to those implementing SAP on generic infrastructure services. Table 3 Hybrid Cloud and Integration Benefits by Provider [7, 8] Cloud Provider Hybrid Latency Reduction (%) Management Complexity Reduction (%) Integration Effort Reduction (%) Configuration Error Reduction (%) Analytics Query Performance Improvement (%) AWS 60 35 30 50 40 Azure 55 40 20 45 35 Google Cloud 50 35 35 40 50 IBM Cloud 45 30 25 60 25 Oracle Cloud 40 25 45 55 30 5. Platform Selection Framework Organizations should consider a comprehensive evaluation framework when selecting a cloud platform for SAP deployments. Research on cloud computing decision frameworks indicates that structured selection approaches significantly increase the likelihood of successful cloud adoption, with enterprises employing formal decision frameworks reporting approximately 19% higher satisfaction with their cloud implementations [9]. The following framework encompasses critical dimensions that collectively determine platform suitability for complex enterprise applications like SAP. 5.1. Current State Assessment A thorough analysis of the existing SAP landscape represents a foundational element of effective platform selection. Decision framework research indicates that organizations conducting comprehensive current state assessments identify approximately 30% more potential migration challenges prior to implementation, substantially reducing project risk [9]. This assessment should begin with a detailed inventory of the existing SAP landscape and version, with particular attention to customizations that may impact cloud compatibility. Studies examining cloud adoption factors reveal that system complexity represents a significant adoption inhibitor, with technical complexity cited by approximately 49% of enterprises as a primary migration concern. Database platform assessment represents another critical component, with platform compatibility varying significantly across cloud providers. Migration complexity analysis indicates that database considerations rank among the top three technical factors influencing platform selection decisions [10]. Database size evaluation holds particular importance, with surveys showing that approximately 43% of organizations identify data volume as a significant consideration when evaluating cloud platforms. Performance characteristics of existing databases provide essential baseline metrics for platform evaluation, with response time requirements serving as critical success criteria for migration initiatives. World Journal of Advanced Research and Reviews, 2025, 26(02), 115-126 123 Performance requirements and service level agreements must be thoroughly documented and prioritized. Cloud decision framework analysis demonstrates that performance expectations represent one of the five most influential factors in platform selection, cited by approximately 40% of enterprises as a primary consideration [9]. Availability requirements deserve particular attention, with surveys indicating that approximately 64% of organizations consider service availability guarantees when evaluating cloud platforms. Systematic documentation of current performance metrics establishes objective baselines against which cloud platform capabilities can be evaluated, reducing the risk of post-migration performance concerns. Integration dependencies frequently represent migration complexity factors that significantly influence platform suitability. Organizational adoption research indicates that integration with existing systems ranks among the top technical considerations, identified by approximately 47% of organizations as a critical evaluation factor [10]. Integration requirement analysis should identify both internal and external system dependencies, with particular attention to real-time integration requirements that may introduce technical constraints. Systematic documentation of integration points enables comprehensive evaluation of platform capabilities against specific technical requirements, substantially reducing the risk of post-implementation integration challenges. 5.2. Future State Vision Clarity regarding migration versus transformation objectives significantly impacts platform selection criteria. Decision framework analysis indicates that strategic alignment represents one of the most influential factors in successful cloud adoption, with approximately 57% of organizations citing alignment with organizational objectives as a critical consideration [9]. Implementation approach decisions should reflect broader business objectives beyond technical considerations, with research showing that transformational initiatives require substantially different platform capabilities compared to straightforward migration efforts. Organizations with clearly defined strategic objectives report approximately 35% higher satisfaction with their platform selections compared to those focusing primarily on technical requirements. Table 4 Critical Factors Influencing SAP Cloud Platform Selection Decisions [9, 10] Selection Factor Reported Impact on Decision Process (%) Cost Considerations 67 Security and Compliance 41 Strategic Alignment 35 Technical Complexity 30 Integration Requirements 47 Innovation Capabilities 35 Cost Optimization 59 Technical Expertise 19 Performance Expectations 64 Future Scalability 38 Geographic Coverage 37 S/4HANA adoption planning represents a pivotal consideration that directly impacts platform selection. Research on cloud adoption factors indicates that future scalability ranks among the top five technical considerations, cited by approximately 38% of organizations as a significant evaluation criterion [10]. Platform capabilities to support nextgeneration SAP technologies should be carefully evaluated, with particular attention to memory-optimized infrastructure required for HANA-based applications. Future-state architecture planning should explicitly address technology evolution requirements, ensuring that selected platforms provide viable migration paths for anticipated application changes. Analytics and innovation requirements increasingly influence platform selection decisions. Decision framework research indicates that approximately 45% of organizations consider innovation capabilities when evaluating cloud platforms, reflecting the growing importance of analytics in business operations [9]. Modern SAP implementations