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Knowledge base Updated: February 5, 2026

Physical Servers and Virtualization: A Comprehensive Guide to x86 and RISC Architectures - From Intel/AMD Processors to IBM Power

x86 and RISC servers differ in performance and application. The choice depends on the organization's needs and application workloads.

Grzegorz Gnych Grzegorz Gnych

In today’s digital world, choosing the right server infrastructure is the foundation of efficient business operations. Processor architecture, virtualization capabilities and system scalability directly affect the operational efficiency, security and maintenance costs of an IT environment. There are three main processor architectures dominating the market today: x86 (Intel, AMD), IBM Power and the increasingly popular ARM, all of which offer distinct approaches to data processing.

This guide examines the differences between these architectures, enabling you to make informed decisions about your IT infrastructure. We will analyze the technical, economic and operational aspects of each solution, focusing on their practical application in modern data centers. Whether you’re planning to upgrade your existing infrastructure or designing a new environment, understanding the advantages and limitations of each architecture is key to optimally aligning the technology with your business needs.

We will also discuss how virtualization transforms the capabilities of all architectures, increasing their flexibility and cost effectiveness. We will present specific use cases where a particular architecture can provide an advantage, taking into account factors such as workload type, availability requirements, security and future scalability.

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What are the differences between x86 and RISC architectures in the context of physical servers?

Historically, the x86 architecture (developed by Intel and AMD) was based on a complex instruction set (CISC - Complex Instruction Set Computing), while architectures such as IBM Power and ARM used a reduced instruction set (RISC - Reduced Instruction Set Computing). However, modern x86 processors have evolved significantly - they now use an internal micro-architecture similar to RISC, which translates complex x86 instructions into simpler micro-operations performed by the processor core. The boundary between CISC and RISC has thus become significantly blurred at the implementation level.

Despite the rapprochement at the microarchitecture level, there are still fundamental design differences. x86 processors have retained backward compatibility with previous generations, which comes with some overhead from supporting older features and instructions. RISC processors, such as the IBM POWER10 and ARM Neoverse N2, were designed without this overhead, allowing more efficient use of transistors for computing tasks. In practice, this translates into differences in power efficiency - according to available benchmarks, POWER10 processors offer an average of 1.5-2x better performance per watt compared to latest-generation Intel Xeon processors for database processing workloads.

At the multithreading level, there are significant implementation differences. Intel Xeon processors support up to 2 threads per core (Hyper-Threading), the latest AMD EPYC also support 2 threads per core (SMT), while IBM POWER10 can support up to 8 threads per physical core. It should be noted, however, that the number of threads alone does not translate linearly into performance gains - the actual throughput of the processor’s subsystems is key. In OLTP tests, a single POWER10 core with 8 threads achieves on average 2.5-3x the throughput of an x86 core with 2 threads, but the difference strongly depends on the nature of the workload and the degree of parallelization.

ARM, as the third major player in the server space, takes an approach that combines high energy efficiency with licensing flexibility. Unlike x86 and IBM Power, ARM operates on a licensing model, where different vendors (such as AWS with Graviton, Ampere Computing, and Fujitsu) can create their own implementations of the architecture. ARM Neoverse N2 processors typically offer lower absolute single-core performance than the top x86 and POWER models, but their low power requirements (35-45W TDP for 64-128 cores) allow for much higher computational density, which is crucial for scalable cloud workloads.

Key differences between today’s server architectures

  • Microarchitecture approximation: Modern x86 processors use an internal structure similar to RISC

  • Multithreading: x86 (Intel/AMD): 2 threads/core, IBM POWER10: 8 threads/core, ARM Neoverse: depending on implementation, typically 1-4 threads/core

  • Power efficiency: ARM > IBM Power > x86 (for most workloads)

  • Memory bandwidth: IBM POWER10: up to 409 GB/s/socket, Intel Xeon Platinum: up to 281 GB/socket, AMD EPYC: up to 410 GB/socket

📚 Read the complete guide: IAM / Zero Trust: Zarządzanie tożsamością i dostępem - od podstaw do Zero Trust

Why do Intel and AMD processors dominate x86 solutions?

The dominance of Intel and AMD processors in the x86 segment is due to a combination of historical, technological and ecosystem factors. Intel, as the creator of the x86 architecture, has shaped market standards for decades, investing huge resources in the development of chip manufacturing technologies. AMD, initially a licensee of Intel’s technology, evolved into a full-fledged competitor, introducing innovations such as the AMD64 64-bit architecture (later adopted by Intel as the Intel 64) and multicore.

A key advantage of the x86 ecosystem is unparalleled software compatibility. Virtually all popular operating systems (Windows, Linux, FreeBSD), business applications, development tools and server solutions are natively available for this architecture. By comparison, IBM Power mainly supports AIX, IBM i and Linux, and server ARM is just developing full support for some enterprise applications. When using popular commercial software, choosing x86 often eliminates the need to recompile applications or use compatibility layers that can introduce performance overhead.

It should be noted, however, that x86 dominance is not solely due to technological superiority - Intel and AMD have different strengths. Intel Xeon processors traditionally offer higher single-threaded performance (important for single-threaded and per-core licensed applications), while AMD EPYC excels with more cores, memory bandwidth and power efficiency. In the latest generations (Intel Xeon Scalable 4th generation vs AMD EPYC 4th generation), the performance differences between the manufacturers have narrowed significantly, and the choice between the two depends mainly on the specific workload profile.

Economy of scale is another important factor. Mass production of x86 processors reduces unit costs and accelerates the innovation cycle. Intel and AMD invest billions of dollars annually in research and development, which translates into regular increases in performance and functionality. At the same time, intense competition between these companies drives innovation and controls prices, which benefits customers. By 2023, AMD has reached about 30% market share in the x86 server market, a significant increase from less than 5% before the introduction of the Zen architecture in 2017.

Interoperability and standardization of components are additional advantages of the x86 ecosystem. Technical standards such as ATX, PCIe, DDR5, and communication protocols allow systems to be composed of parts from different manufacturers. This flexibility allows organizations to optimize performance and costs by selectively choosing the components that best fit their needs, and makes it easier to expand and upgrade systems without having to replace the entire infrastructure.

What advantages do IBM Power servers offer over x86 solutions?

IBM Power servers are distinguished by high single-core performance and multi-threading efficiency, which translates into better support for demanding business applications. According to SAP Standard Application Benchmarks tests, the POWER10 single core (3.65-4.0 GHz) delivers approximately 1.5-1.8x the performance of a comparable Intel Xeon Platinum (2.9-3.5 GHz). This performance advantage has significant implications for per-core licensed applications - a system with 16 POWER10 cores can replace an x86 system with 24-32 cores at similar application performance, resulting in lower licensing costs.

The memory architecture in IBM Power servers provides another significant advantage in certain scenarios. POWER10 offers up to 16TB of RAM per socket (vs. 6TB for Intel Xeon 4th generation and 9TB for AMD EPYC 4th generation) and significantly higher memory bandwidth. The practical effect is better performance for memory-intensive applications such as in-memory databases (e.g. SAP HANA), where POWER10 can achieve 20-35% better response times than comparable x86 configurations for large data sets (>8TB).

Security at the hardware level is an area where both x86 and IBM Power offer advanced solutions, but with different implementation priorities. IBM Power implements PowerVM Security Hypervisor and Protected Execution Facility technology, which provide virtual machine isolation and protection against hypervisor attacks. Intel offers SGX (Software Guard Extensions) for creating secure memory enclaves and TME/TDX (Total Memory Encryption/Trust Domain Extensions) for in-memory data protection. AMD provides SEV (Secure Encrypted Virtualization) and SEV-SNP for similar purposes. The main difference is that IBM Power security is more deeply integrated into the hypervisor (PowerVM), while x86 solutions offer more flexibility for integration with different hypervisors.

It should be noted, however, that IBM Power’s advantages come with significant tradeoffs. The biggest limitation is the higher initial cost - IBM Power servers are typically 30-70% more expensive than comparable x86 configurations with a similar number of cores. Additionally, the software ecosystem for IBM Power is more limited - many applications are not natively available for this platform or require special adaptation. The availability of professionals with Power systems administration experience is also much lower than for x86, which can lead to higher personnel costs and recruitment difficulties.

Comparison of key parameters of the latest server processors

ParameterIntel Xeon Platinum 8490HAMD EPYC 9654IBM POWER10 (10-core)AWS Graviton3
Number of cores (max)609615/slot (30/processor)64
Threads/core2281
Base frequency1.9 GHz2.4 GHz3.0 GHz2.6 GHz
Turbo/Max3.5 GHz3.7 GHz4.0 GHzN/A
L3 cache105 MB384 MB120 MB32 MB
TDP350W360W250-300W/socket~100W
Max. memory/processor6 TB9 TB16 TB512 GB
Memory bandwidth281 GB/s410 GB/s409 GB/s~200 GB/s

*Note: Exact values may vary depending on the specific implementation and system configuration.

How does virtualization improve the efficiency of x86-based infrastructure?

Virtualization has fundamentally changed the way x86 infrastructure is used, enabling the consolidation of multiple physical servers on a single hardware platform. Today’s virtualization technologies - Microsoft Hyper-V, KVM or Xen - use hardware support for virtualization (Intel VT-x, AMD-V), achieving near-native performance (95-98% system performance without virtualization for most workloads).

Today’s x86 virtualization platforms offer extensive resource management features. Similar functionality is offered by Microsoft System Center VMM and open platforms like OpenStack. Contrary to popular belief, today’s x86 solutions offer considerable flexibility in resource allocation - vSphere 8.0 allows processor allocation at granularity of up to 1/8 core (comparable to IBM PowerVM’s 0.125 core), though still inferior to PowerVM’s granularity (0.01 core).

x86 virtualization has evolved well beyond basic resource consolidation. Technologies such as Microsoft SDN (Software-Defined Networking) enable advanced network virtualization, creating software overlays above the physical infrastructure. Software-Defined Storage (SDS) solutions like Microsoft Storage Spaces Direct and Ceph allow the creation of flexible, distributed storage systems using standard disks in x86 servers. These functionalities enable the implementation of full Software-Defined Infrastructure (SDI) on standard x86 hardware, offering flexibility comparable to public clouds.

However, it is important to note the limitations of x86 virtualization in the context of highly demanding workloads. In scenarios requiring very high I/O throughput, extremely low latency or maximum computing performance, virtualization introduces a measurable overhead. For example, database applications with intensive I/O operations can experience 5-15% performance degradation in a virtualized environment compared to a bare-metal installation. In such cases, the x86 infrastructure may require additional optimizations, such as SR-IOV (Single Root I/O Virtualization) for networking or dedicated GPU cards with vGPU technology for compute workloads. Alternatively, for the most critical workloads, organizations can consider platforms optimized for specific use cases, such as IBM Power for intensive database workloads or servers with GPU gas pedals for AI/ML workloads.

How does IBM Power’s RISC architecture affect computing performance?

Today’s IBM Power processors, although derived from the RISC tradition, represent a highly advanced hybrid computing architecture. POWER10 uses a 7nm technology process, offers up to 15 cores per chip (vs. 60 for the Intel Xeon Platinum 8490H or 96 for the AMD EPYC 9654), but the key difference lies in the processor’s internal organization. Each POWER10 core can execute up to 8 threads simultaneously, supports wider vector units (4x512-bit VSX) and has advanced units for floating-point operations.

Comparing raw performance, a single POWER10 core in standard benchmarks (SPEC CPU2017) performs comparably to the latest Intel Golden Cove and AMD Zen4 cores, but in specialized database benchmarks (such as SAP HANA BWH) can offer a 20-30% advantage. The difference is mainly due to two factors: higher memory bandwidth (thanks to the Open Memory Interface with up to 409 GB/s per socket) and advanced instruction prediction and processing mechanisms that better handle irregular memory access patterns typical of database applications.

The IBM Power architecture also offers specialized hardware gas pedals integrated into the processor that significantly improve performance for specific workloads:

  • Matrix Math Accelerator (MMA) - units dedicated to matrix and tensor operations that accelerate AI/ML calculations up to 20x compared to standard vector instructions, offering performance similar to dedicated GPUs for some machine learning algorithms

  • Encryption/Decryption Engine - Dedicated cryptographic units reaching up to 40 GB/s per core for AES-GCM operations, which minimizes the overhead associated with encrypting data on the fly

  • Compression Accelerator - hardware acceleration of data compression and decompression, increasing the effective bandwidth of memory and I/O

These hardware gas pedals provide a significant advantage for specific workloads, but their effective use requires software optimization. Applications unable to take advantage of these features will not reap the full benefits of the Power architecture.

It should also be noted that x86 processors are also evolving into specialized gas pedals. Intel introduced Advanced Matrix Extensions (AMX) in its 4th-generation Xeon processors for accelerated AI computing, and AMD is developing similar technologies. The difference lies mainly in the degree of integration of these functions into the main processor core - in IBM Power they are more deeply integrated into the execution pipeline, while in x86 they often function as separate functional units.

What to look for when choosing between multicore and single-threaded performance?

The choice between a high number of cores and high single thread performance is a key architectural decision, the implications of which reach far beyond a simple calculation of aggregate computing power. Amdahl’s law defines a fundamental limitation of parallel scaling - if only 95% of an application can be parallelized, the maximum theoretical performance increase is limited to 20x, regardless of the number of cores added. In practice, many business applications contain significant chunks of sequential code, making single thread performance a critical parameter.

Modern databases present varying scaling characteristics. PostgreSQL, due to its multi-process architecture, effectively uses multiple cores for parallel queries, but inter-process synchronization can become a bottleneck when the number of cores is very high (>64). Oracle Database uses an adaptive architecture that scales effectively both vertically and horizontally, but per-core licensing can make solutions with fewer, more powerful cores (like IBM Power) more economically viable. Microsoft SQL Server offers similar characteristics, with its performance being particularly sensitive to memory bandwidth.

Concrete figures help illustrate the economic implications of these differences. An example OLTP database application requiring 100,000 transactions per second can be supported by:

  • System with 4 IBM POWER10 processors (10-core), 40 cores in total, with Oracle Enterprise Edition license: about $400,000 for Oracle licenses (40 cores × $10,000/core)
  • System with 4 x86 processors (64-core), total 256 cores, with Oracle Enterprise Edition license: about $1,280,000 for Oracle licenses (256 cores × $5,000/core, with 50% discount for multicore)

Despite the higher cost of IBM Power hardware (by about $150,000-200,000), the total cost of the system over a 3-year horizon can be 30-40% lower due to savings on licenses.

Load characteristics should also be considered. Processor cache-intensive (cache-friendly) applications, like most web services and microservices, typically scale better horizontally and make more efficient use of architectures with more cores. In contrast, applications with irregular memory access patterns, such as graph analytics and some ML algorithms, often achieve better performance on processors with larger caches and higher single-thread performance.

Practical performance tests show that:

  • For typical OLTP applications: A single POWER10 core handles on average 2-2.5x more transactions than an x86 core (Intel/AMD latest generation)

  • For analytics applications: POWER10 advantage reduces to 1.3-1.8x per core

  • For container and microservices applications: The performance difference between architectures is minimal (0.9-1.2x)

How do virtualization technologies work with different processor architectures?

Virtualization technologies have evolved in parallel with processor architectures, creating platform-specific ecosystems. On the x86 platform dominates the enterprise segment, offering advanced features like DRS (Distributed Resource Scheduler), Storage vMotion and NSX (network virtualization). Microsoft Hyper-V provides deep integration with the Windows ecosystem, while KVM and Xen provide the foundation for many open-source and commercial solutions, including cloud platforms. As they have matured, x86 hypervisors have developed high availability, performance and security options, minimizing the initial technological advantage of specialized platforms.

PowerVM, the native hypervisor for IBM Power, offers features that set it apart in some respects. Its resource allocation granularity (0.01 CPU core) exceeds that of (1/8 core) or Hyper-V (1 core), which can lead to more efficient resource utilization in environments with many small VMs. Active Memory Sharing enables dynamic memory sharing between logical partitions, which can increase consolidation density by 20-30% compared to standard x86 virtualization. PowerVM also offers advanced reliability features, such as dedicated service coprocessors that monitor and manage infrastructure independently of the main processor.

In the context of ARM virtualization, the situation is more complex. AWS Nitro for Graviton instances uses a specialized architecture with minimal overhead, but is a proprietary solution. KVM on ARM has gained significantly in maturity, but some advanced features available on x86 (such as SR-IOV or live migration for specific instances) may have limitations. Virtualization on ARMv8 and newer generations benefits from virtualization extensions, achieving performance comparable to x86 platforms.

Specific performance comparisons show interesting differences:

  • Virtualization overhead for standard web workloads: : 3-5%, Microsoft Hyper-V: 4-7%, PowerVM: 2-4%, KVM on ARM: 3-6%

  • Consolidation density (number of VMs/physical server under typical office workloads): PowerVM typically achieves 15-25% higher density than vSphere on comparable x86 hardware.

  • I/O throughput in virtualized environments: PowerVM offers a 10-20% advantage for intensive I/O operations due to deeper integration with the processor architecture

An important aspect of the evolution of virtualization is the trend toward abstraction of the hypervisor technology itself. Containers (Docker, Kubernetes), by abstracting the operating system level rather than the hardware, offer a lightweight virtualization solution that runs effectively on all the architectures in question. OpenShift, which runs on x86, IBM Power and ARM, provides a consistent container environment regardless of the underlying architecture, enabling organizations to implement multi-architecture strategies without significant application modification.

Why do IBM Power servers perform better in high-availability environments?

IBM Power servers offer extensive high availability features, but it is worth comparing them objectively with the advanced solutions available for x86 platforms. The IBM Power architecture implements redundancy at multiple levels - from duplicated internal components (power supplies, fans, memory controllers) to advanced error detection and correction mechanisms for the processor. POWER10 offers Extended Error Handling for memory, which can correct most multi-bit errors without affecting system performance, while x86 processors are typically limited to single-bit error correction (although the latest generations of AMD EPYC and Intel Xeon also extend these capabilities).

Comparing specific reliability parameters:

  • Mean time between failures (MTBF) for IBM Power Scale-Out servers: >100,000 hours

  • MTBF for x86 enterprise servers (Dell PowerEdge, HPE ProLiant): 70,000-90,000 hours

  • System availability (including planned downtime): IBM Power: typically >99.997%, x86 enterprise servers: typically >99.99%.

These differences may seem small, but they translate into significant business implications - the difference between 99.99% and 99.997% availability equals almost 30 minutes of additional downtime per year.

Live Partition Mobility (LPM) enables the migration of running logical partitions between physical servers without interrupting applications. Similar functionality is offered by vMotion in Live Migration in Hyper-V, but LPM is integrated into the firmware and does not require an additional software layer, which can lead to lower latency during migration. In benchmark tests, migrating a virtual machine with 64GB of RAM:

  • PowerVM LPM: 30-45 seconds with negligible impact on the application (bandwidth drop <5%)

  • Hyper-V Live Migration: 50-80 seconds with comparable impact

It is worth noting, however, that x86 platforms offer clustering solutions comparable to PowerHA. Windows Server Failover Clustering, Linux Pacemaker HA provide automatic failure detection and switching between cluster nodes. The difference lies mainly in the degree of integration with the hardware platform - PowerHA is more tightly integrated with IBM Power firmware, which can speed up failure detection at the hardware level.

A key advantage of IBM Power in high availability scenarios is Advanced System Recovery, which monitors system health and automatically isolates faulty components, keeping applications running. This mechanism can detect and respond to component degradation before it leads to failure, significantly reducing the frequency of unplanned downtime. Similar features in x86 platforms (such as HPE iLO, Dell iDRAC and Intel Node Manager) provide basic diagnostics, but do not offer a comparable level of automatic protection and fault isolation.

How do you compare the costs of maintaining x86 and IBM Power infrastructure over a 5-year horizon?

A reliable TCO analysis requires consideration of all relevant cost components. The table below shows a detailed comparison for an example scenario of implementing a database system supporting critical business applications, with a requirement to support 100,000 transactions/sec:

Cost componentIBM Power (4x Power S1022)x86 (8x enterprise-class servers)
Cost of equipment$450,000 - $550,000$280,000 - $350,000
System software$120,000 - $150,000 (PowerVM, AIX)$80,000 - $120,000 (RHEL)
Database licenses (Oracle EE)$400,000 (40 cores × $10,000)$1,280,000 (256 cores × $5,000)
Maintenance/support (3 years)$250,000 - $300,000$150,000 - $200,000
Energy consumption (3 years)$45,000 (60kW × $0.15/kWh)$90,000 (120kW × $0.15/kWh)
Cooling (3 years)$22,500 (50% of energy costs)$45,000 (50% of energy costs)
Data center space$36,000 (8U × $1,500/year)$54,000 (12U × $1,500/year)
IT staff (3 years)$450,000 (1.5 FTE × $100,000)$300,000 (1 FTE × $100,000)
TOTAL COST (3 YEARS)$1,773,500 - $1,953,500$2,279,000 - $2,439,000
Cost per transaction$5.92 - $6.51 / 1000 trans.$7.60 - $8.13 / 1000 trans.

*FTE - Full Time Equivalent (FTE).

Sensitivity analysis shows how different assumptions affect TCO results:

  • If database licensing costs are 50% lower (e.g., using open-source): the x86 platform becomes 15-20% cheaper

  • With a 50% increase in energy costs: the difference in favor of IBM Power increases by an additional 2-3%

  • If the performance requirements increase by 50%: the difference in favor of IBM Power increases to 25-30%

The non-financial aspects of TCO, often overlooked in analyses, can have a significant impact on actual costs:

  • Risk of business downtime: IBM Power’s higher reliability can reduce the risk of costly failures

  • Business flexibility: The ability to scale quickly in response to changing workloads can translate into tangible business benefits

  • Readiness for future requirements: The ability of the platform to adapt to new workloads (e.g., AI/ML) without a major infrastructure overhaul

It’s worth noting that ARM platforms (like AWS Graviton) can offer even more favorable TCO in cloud environments, with savings of up to 30-40% compared to x86 instances of similar performance, mainly due to lower energy and licensing costs.

In what business scenarios can choosing RISC be a strategic advantage?

Today’s RISC implementations, such as IBM Power and ARM, offer unique advantages in specific business scenarios that should be considered in the context of an organization’s specific needs.

  • Intensive transactional processing (OLTP)

Banking: Systems processing hundreds of thousands of transactions per second, where IBM Power provides 30-40% higher throughput per core than x86

  • E-commerce: Servers handling peak loads during sales or promotions, where IBM Power performance stability even at 95%+ system utilization outperforms x86

  • Case in point: ING Bank achieved a 35% reduction in transaction processing latency and a 45% increase in throughput after migrating from x86 to IBM Power

  • Analytics platforms and Big Data

Systems powering real-time decision-making processes, where the performance of IBM Power with SAP HANA exceeds that of x86 platforms for large data sets by 20-40%

  • Predictive analytics in telecommunications, where POWER10’s ability to handle 2-3x larger data sets in memory per server compared to x86 translates into more accurate models

  • Financial institutions using real-time risk analytics, where workloads heavily dependent on memory bandwidth benefit from IBM Power architecture

  • Business-critical solutions

Airline reservation systems: Benchmark tests show 15-25% lower and more predictable response times on IBM Power

  • Supply chain management systems requiring continuous availability, where IBM Power’s fault tolerance features result in less unplanned downtime (45% less total downtime per year on average)
  • A concrete example: A European telecom operator reduced unplanned downtime by 72% after migrating critical billing systems to IBM Power

In the context of ARM platforms, strategic applications include:

  • Cost-optimized cloud infrastructure

Webservers and APIs: AWS reports 40% lower cost and 20% better performance for web applications on Graviton3 vs x86

  • Microservices supporting high traffic volumes but with predictable patterns, where lower ARM instance costs (20-40% savings) directly translate into TCO reduction
  • Edge Computing

IoT processing closer to the source, where ARM’s energy efficiency (2-3x better than x86) enables higher computational density with energy constraints

  • Intelligent video surveillance and analysis systems where performance/wattage is a key factor
  • HPC (High Performance Computing) for specific workloads

Weather and climate simulations, where ARM architecture (e.g., Fujitsu A64FX) offers up to 2-3x better energy efficiency than traditional x86 systems

  • Genomic sequencing, where specialized ARM chips with gas pedals achieve a more favorable performance-to-cost ratio

It should be noted that for most standard IT workloads, especially in smaller organizations, x86 platforms still offer an optimal balance between performance, cost and ease of deployment. The advantage of RISC architectures is mainly revealed in specialized workloads with high requirements or at scale, where even small performance differences translate into significant savings.

How does hardware security differentiate x86 and IBM Power architectures?

Today’s processor architectures implement advanced security mechanisms at the hardware level, but with different priorities and implementation approaches. A comparison of the main security technologies shows the areas of specialization of each platform:

Safety functionIBM POWER10Intel Xeon (Ice Lake/Sapphire Rapids)AMD EPYC (Milan/Genoa)ARM Neoverse
Memory encryptionFull memory encryption with unique keys per partitionTME (Total Memory Encryption), MKTME (Multi-Key TME)SME (Secure Memory Encryption), TSME (Transparent SME)Memory Tagging Extension (MTE)
Secure virtualizationProtected Execution Facility, isolation at the firmware levelTDX (Trust Domain Extensions)SEV (Secure Encrypted Virtualization), SEV-SNP (Secure Nested Paging)Realm Management Extension (RME)
Safe enclavesN/A (different approach)SGX (Software Guard Extensions)SEV-ES (Encrypted State)Confidential Compute Architecture (CCA)
Safe bootSecure Boot with verification in hardwareBoot Guard, UEFI Secure BootHardware Validated BootTrustZone Secure Boot
Cryptographic accelerationDedicated units per core (25-40 GB/s/core)AES-NI, VAES (Vector AES), QATAES-NI, SHA ExtensionsCryptographic Extension

IBM Power architecture is distinguished by its approach to isolating virtual environments. The Protected Execution Facility (PEF) enables the creation of secure partitions where neither the hypervisor administrator nor the operating systems of other partitions can access the memory or processor state of the secure partition. Data is encrypted with a unique key generated in the secure hardware component (Trusted Platform Module) and can never be accessed in unencrypted form outside the processor. In security testing, attempts to access the memory of the protected partition from within the privileged hypervisor are effectively blocked.

Intel and AMD implement similar functionality through TDX and SEV-SNP, respectively, but with some architectural differences:

  • Intel TDX uses VT (Virtualization Technology) extensions and the new TDR (Trust Domain Root) concept to isolate virtual machines

  • AMD SEV-SNP uses a dedicated hardware security processor (AMD PSP) to manage encryption keys and security policies

  • Both x86 solutions were developed much later than PowerVM Security Hypervisor, but in their latest implementations they offer comparable levels of protection

In practical tests of resistance to side-channel attacks (timing attacks, cache attacks):

  • POWER10 demonstrates superior resilience through isolation at the cache and memory levels

  • AMD EPYC with SEV-SNP offers better protection than Intel TDX for many attack scenarios

  • All platforms retain some vulnerability to sophisticated speculative execution attacks, but with varying degrees of exposure.

It’s worth noting that ARM Neoverse processors (used in AWS Graviton, Ampere Altra) implement their own security mechanisms, including Confidential Compute Architecture (CCA) and Memory Tagging Extension (MTE), which provide advanced protection against memory and shadow attacks in virtualization. ARM implementations often provide better energy efficiency for security functions, with less performance overhead for cryptographic operations.

For organizations subject to stringent compliance requirements (such as banks or government institutions), differences in security implementation can have significant implications. IBM Power traditionally provides more comprehensive documentation and security certifications (FIPS 140-2, Common Criteria), which can simplify audit and compliance validation processes.

How to effectively manage heterogeneous environments with x86 and RISC?

Today’s organizations often maintain heterogeneous IT environments, using different processor architectures to support disparate workloads. Effectively managing such a complex ecosystem requires a strategic approach that begins with fine-tuning workloads to the appropriate platforms. Applications with high performance requirements, critical databases and transactional processing systems can be routed to the IBM Power platform, while standard web services, development environments or applications with lower performance requirements can be served by x86 infrastructure. This segmentation of workloads maximizes the advantages of each architecture, while optimizing the total cost of ownership of the IT infrastructure.

Standardization of management and monitoring tools is key to effectively operating a heterogeneous environment. Modern infrastructure management solutions, such as IBM Cloud Pak for Multicloud Management or offer a unified interface for managing different hardware platforms. Similarly, monitoring platforms such as Zabbix, Nagios or Prometheus can integrate data from different systems to provide a holistic view of infrastructure health. This unification of tools greatly simplifies day-to-day management of the environment, reduces the need for specialized expertise for each platform, and allows for faster detection and resolution of problems, regardless of which architecture they occur on.

Containerization and orchestration technologies, such as Docker and Kubernetes, play a key role in creating a consistent application environment across architectural differences. These platforms allow applications with their dependencies to be packaged into portable units that can run on different operating systems and hardware architectures. Red Hat OpenShift, which runs on both x86 and IBM Power, enables a unified container environment that spans both architectures. This infrastructure abstraction significantly simplifies the process of application deployment, lifecycle management and scaling, regardless of the underlying hardware architecture.

Managing software licenses in a heterogeneous environment requires special attention, as it can significantly affect the total cost of ownership. Many commercial business applications, especially databases and ERP systems, use licensing models based on the number of processor cores. In such a model, strategic placement of workloads between platforms with different single-core performance can lead to optimized licensing costs. For example, applications licensed on a per-core basis can be routed to the IBM Power platform, where the higher performance of a single core allows a comparable workload to be supported with fewer licenses. At the same time, applications with end-user or instance-based licenses can be efficiently supported on the x86 platform. Such strategic load allocation based on the licensing model can lead to significant savings in the long term.

Key aspects of heterogeneous environment management

  • Workload segmentation: Strategically matching applications to the optimal hardware platform

  • Unification of management: Standardization of monitoring and administration tools across architectural differences

  • Containerization: Using container technologies to abstract infrastructure

  • License Optimization: Strategic load placement that takes licensing models into account

The future of x86 and RISC architecture in the era of digital transformation

The dynamic development of computing technologies and the evolution of business requirements are constantly shaping the IT infrastructure landscape. The x86 architecture is evolving, introducing RISC-like solutions - Intel Golden Cove and AMD Zen4 internally incorporate many RISC features (execution pipeline, out-of-order execution, register renaming). At the same time, IBM Power and ARM are introducing specialized gas pedals and vector units previously associated with x86. The latest SPEC CPU2017 benchmarks show diminishing differences in per-core performance: top Intel Xeon and AMD EPYC models achieve 85-95% of POWER10 performance in whole-core performance tests (SPECrate2017_int_base).

Artificial intelligence and machine learning are becoming key workloads driving innovation in processor architectures. Performance comparisons for popular ML frameworks:

  • TensorFlow (inferencing): POWER10 with Matrix Math Accelerator achieves 15-30% advantage over 4th generation Xeon with similar number of cores

  • PyTorch (training): x86 processors with dedicated GPUs still offer best performance-to-price ratio

  • ARM-based Neoverse with SVE2 (Scalable Vector Extension) acceleration offers best energy efficiency (2-3x better than x86) for specific inferencing models

All major architectures are investing in solutions specialized for AI:

  • Intel: AMX (Advanced Matrix Extensions) at Sapphire Rapids

  • AMD: CDNA/RDNA for AI computing in Instinct MI300 processors (hybrid CPU+GPU)

  • IBM: Matrix Math Accelerator in POWER10

  • ARM: SVE2 and dedicated tensor units in Neoverse V1/V2

The heterogeneous model and hardware specialization are becoming the dominant trend. Instead of choosing a single architecture, organizations are increasingly implementing a “best tool for a specific task” model:

  • Critical databases on IBM Power (better reliability, fewer licenses)

  • Standard enterprise applications on x86 (wide software availability, lower costs)

  • AI/ML workloads on specialized gas pedals (GPU, TPU, etc.).

  • Edge (edge) and power-saving applications on ARM (better performance/watt)

Cloud technologies and containerization are further driving this trend, providing a consistent operating environment regardless of architecture. In 2023, AWS expanded its Graviton (ARM) offering with more than 25 new instance types, the fastest growth of any instance type, indicating the growing popularity of alternative architectures in the mainstreamic. Closer integration of hybrid clouds with on-premise data centers will further blur the lines between architectures.

Key findings - how to choose the optimal architecture for your organization?

The choice between x86, IBM Power and ARM architectures should be based on a multidimensional analysis of your organization’s specific requirements and priorities. Below is a structured approach to making this decision:

  • Analysis of application performance characteristics

For workloads with predominantly single-threaded operations (e.g. SAP, Oracle E-Business Suite):

IBM Power offers 1.5-1.8x performance advantage per core

  • If licensing is per core, this can translate into 30-50% savings
  • For highly parallelized applications (Web, Stateless):

x86 (especially AMD EPYC) offers best performance/price

  • ARM (AWS Graviton) can provide the best performance/watt (30-40% lower cost in the cloud)
  • For memory-intensive applications (SAP HANA, analytics):

IBM Power offers the largest memory capacity per socket (16TB vs 9TB EPYC vs 6TB Xeon)

  • Memory bandwidth: AMD EPYC ≈ IBM Power > Intel Xeon > ARM.
  • TCO calculation with all relevant components

Hardware: IBM Power more expensive by 40-70% than comparable x86 servers

  • System software: PowerVM/AIX more expensive by 20-40% than vSphere/RHEL

  • Application licensing: potential savings of 30-60% on IBM Power for software licensed per core

  • Energy and cooling: IBM Power and ARM offer 30-50% better energy efficiency than x86

  • IT staff: x86 offers lowest cost due to universality of competence

  • Assessing the software ecosystem and dependencies

Application Compatibility:

x86: virtually universal compatibility (Windows, Linux, FreeBSD)

  • IBM Power: AIX, IBM i, Linux (RHEL, SLES, Ubuntu)

  • ARM: growing support for Linux, limited for enterprise applications

  • Developer tools and libraries:

For most applications Java, Python, NodeJS: all platforms offer good support

  • For legacy applications, especially commercial ones: x86 support is widest
  • Prioritization of security and reliability requirements

If maximum reliability is required (finance, telecommunications):

IBM Power offers the highest single reliability (99.997% vs 99.99% for x86)

  • Lowest MTTR (Mean Time To Recovery): IBM Power < x86 < ARM
  • For security requirements:

Protection against attacks: IBM Power ≥ AMD EPYC with SEV-SNP > Intel Xeon with TDX

  • Security certifications: IBM Power offers the broadest portfolio of certifications (FIPS, Common Criteria)
  • Analysis of long-term strategy

Platform lifecycle:

IBM Power: typically 5-7 years (IBM support)

  • x86: typically 3-5 years (faster technology evolution)

  • ARM: no fixed cycle for servers, but rapid development

  • Future workloads (AI/ML, analytics, edge):

All platforms are investing in AI gas pedals, but with different approaches

  • For edge computing: ARM offers the best energy efficiency

The decision-making process should be supplemented with proof-of-concept and benchmarks for the organization’s key applications. Comparing performance, TCO and compatibility on actual production workloads will provide the most reliable data for decision-making.

Recommendations for different types of organizations

  • Large enterprises with critical business applications: Hybrid solution - IBM Power for critical databases and transactional applications, x86 for standard workloads

  • Cost-oriented organizations with standard applications: x86 platform as a base, with consideration of ARM in the cloud for stateless workloads

  • Technology companies with advanced AI/ML workloads: Heterogeneous model with x86+GPU for training, with potential use of IBM Power or ARM for inferencing

  • Small and medium-sized enterprises: x86 as the most universal solution, with reasonable costs and availability of competence

Summary - the place of x86 and RISC architectures in the modern data center

The modern data center rarely relies solely on a single processor architecture - instead, organizations are increasingly implementing heterogeneous strategies that leverage the advantages of different platforms. The x86 architecture (Intel Xeon, AMD EPYC) remains the cornerstone of most data centers due to its versatility, rich software ecosystem and expert availability. Benchmarks show that the latest generation of x86 processors offer competitive performance for most standard workloads, and intense competition between Intel and AMD is driving innovation and controlling prices.

IBM Power positions itself as the premium platform for critical business workloads where performance, reliability and security are critical. Real-world deployments show that in scenarios such as large databases (>8TB), intensive transactional processing or analytical systems, IBM Power can offer 15-30% better performance and 30-40% lower total cost of ownership (after accounting for licensing savings) compared to x86 solutions. At the same time, higher initial cost and lower availability of specialists are significant barriers to adoption, especially for smaller organizations.

ARM, represented by solutions like AWS Graviton, Ampere Altra and Fujitsu A64FX, is dynamically gaining ground, especially in the context of cloud and edge computing. Benchmark tests show that ARM-based instances can offer a 20-40% better performance-to-cost ratio for a wide range of workloads, especially those that can be effectively parallelized. Availability of some commercial applications and enterprise tools remains a limitation, but the situation is improving rapidly thanks to growing interest from large software vendors.

Based on current trends, the future likely belongs to heterogeneous infrastructure, where different architectures coexist within a cohesive operating environment. Technologies such as containers (Docker, Kubernetes, OpenShift) and multi-cloud orchestration create abstraction over hardware differences, allowing organizations to choose the optimal platform for each type of workload. At the same time, all major architectures are evolving toward greater specialization, integrating dedicated gas pedals for workloads such as AI/ML, data analytics and cryptography, further blurring traditional boundaries between processor categories.

Ultimately, success in the modern data center depends not so much on choosing a single “best” architecture, but on the ability to strategically align technology with specific business needs and effectively manage a heterogeneous environment. Organizations that can objectively assess the advantages and limitations of each platform in the context of their unique requirements will be able to build IT infrastructures that effectively support business goals at an optimal performance-to-cost ratio.

The place of architectures in the modern data center

  • Specialization and acceleration: all architectures are moving towards dedicated solutions for AI/ML and advanced analytics

  • Hybrid approach: Leveraging the advantages of different architectures depending on the specific workloads

  • x86 as the foundation: Ideal for standard workloads, development environments and containerized applications

  • IBM Power for critical applications: Optimized for transactions, databases, analytics and AI requiring maximum reliability

  • ARM for cost efficiency: Growing importance in cloud and edge computing

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