What is a Hyperscaler Cloud? Top Features and Examples

When developers talk about hyperscaler cloud providers, they’re usually referring to Amazon Web Services (AWS), Microsoft Azure, and Google Cloud. Hyperscale market share accounts for 63% of global cloud infrastructure, with AWS holding 29%, Azure at 29%, and Google Cloud with 13% as of Q3 2025, according to Statstia. Hyperscale enterprise adoption is even higher, with most large organizations using at least one hyperscaler as a primary or secondary cloud. Widespread adoption stems from hyperscalers’ sheer scale and breadth, encompassing global regions, massive compute capacity, and an ever-expanding catalog of managed services for data, AI/ML, security, and hybrid workloads.

Many digital-native enterprises may default to using well-known hyperscaler infrastructure, but it’s hardly the only option. There are numerous cloud providers that cater to specific markets, industries, and regions, collectively offering a diverse array of cloud services to meet the varied needs of global users. Specialized cloud providers, like DigitalOcean, can offer tailored solutions and personalized support in areas that hyperscalers might not prioritize due to their vast scale.

What is a hyperscaler cloud in cloud computing?

A hyperscaler cloud is a cloud solutions provider that operates at an incredibly large scale to meet enterprise computing and data management requirements. Its name derives from a data-processing method that allows the system architecture to scale as system demands grow. This cloud infrastructure type is supported by hyperscaler data centers that operate globally across multiple availability zones and regions.

Doing so provides scalability and redundancy for enterprise use cases, such as AI, machine learning, and extensive virtual machine deployments. Hyperscaler cloud providers fully manage backend infrastructure, allowing organizations to focus on application development and deployment while providing access to technical support when needed.

Benefits of hyperscaler cloud platforms

Hyperscalers like AWS, Azure, and GCP offer scalability, global reach, and an extensive array of services. These cloud providers are used by a wide range of businesses, from small businesses to large enterprises, and are often well-suited for teams with dedicated DevOps and FinOps experts who can navigate complex configurations, or organizations already tied to a specific ecosystem—like enterprises standardized on Microsoft technologies that benefit from Azure’s deep integrations.

Companies often choose these cloud providers to match extensive infrastructure needs, as navigating their pricing structures can be challenging (leading to bill shock) and less cost-effective for smaller companies. The main benefits typically are:

• Scalability: Hyperscaler clouds are designed to scale up or down to meet demand. They offer virtually unlimited computing resources, enabling businesses to scale their applications and services rapidly to meet changing demands without worrying about hardware constraints.

• Global availability: Hyperscaler clouds are designed to be highly available and have a large number of data centers located around the globe, which can mean more redundancy for your cloud application if it’s hosted across data centers.

• Security: Providers invest in infrastructure redundancy, disaster recovery, and cybersecurity, which helps ensure high levels of service availability and data protection.

Challenges of hyperscaler cloud computing

While hyperscale clouds can meet the scalability needs of large businesses, pricing complexity, potential vendor lock-in, data transfer costs, and regulatory considerations warrant careful evaluation. This is why some companies decide to evaluate hyperscaler alternatives, such as DigitalOcean or other tailored cloud providers, to run their workloads; these options can frequently offer more specialized, budget-friendly setups.

When comparing hyperscalers to other specialty cloud providers, assess factors such as service offerings, cloud scalability, pricing models, support, and cloud security and compliance measures. For instance, hyperscalers offer global reach and diverse services but might lack personalization. Alternative providers may offer tailored solutions, better support, and cost optimization strategies. Understanding these differences will help you make an informed decision and ensure a seamless cloud experience aligned with your specific requirements and strategic goals. The main challenges are:

• Complexity: Hyperscaler clouds offer a wide range of features and services, which can be overwhelming for some users. Their extensive customer base might lead to difficulty obtaining personalized support and prompt responses, particularly for smaller businesses.

• Vendor lock-in: There’s a risk of becoming reliant on one vendor for the majority of your computing needs, and you may have difficulty migrating to another cloud provider from a hyperscaler. This lock-in can limit flexibility and make it challenging for organizations to take advantage of innovations and cost savings available from other cloud service providers.

• Unpredictable pricing: Fluctuating costs and seemingly hidden fees for egress, managed services, and data transfers make budgeting at scale challenging, often resulting in unexpected expenses. Hyperscalers tend to bill according to percentage pricing, where you pay a percentage of your cloud costs, which may likely change over time and be more difficult to forecast than defined usage-based pricing tiers.

Hyperscaler cloud providers

Cloud hyperscalers facilitate quick access to a large amount of computing power for enterprise-level workloads without the need to set up your own infrastructure. They also offer integrated options for managed services and technical support. The five major hyperscaler cloud providers include:

*The “best for” information reflects an opinion based solely on publicly available third-party commentary and user experiences shared in public forums. It does not constitute verified facts, comprehensive data, or a definitive assessment of the service.

Amazon Web Services (AWS) featuring global availability

AWS’s hyperscaler cloud provides global infrastructure in 120 availability zones with 38 geographic regions for its users. Alongside this cloud offering, it includes 263 products and services such as containers, developer tools, networking, and content delivery, as well as machine learning and AI. You can choose from a variety of cloud configurations, including cloud-native, serverless, on-premises, and edge computing. All of this is backed by AWS customer support, which offers free and paid plans with varying response times and levels of technical support, but can often become costly very quickly with AWS’s percentage-based pricing model.

Core offerings:

• Compute: Amazon EC2 services, container services, AWS Lambda, AWS Outposts, and AWS Local Zones

• Storage: Amazon EBS (block), Amazon FSX and EFS (file), and Amazon S3 and S3 Glacier (object)

• Networking: Amazon VPC, AWS Direct Connect, AWS Cloud WAN, Amazon CloudFront, AWS Global Accelerator, and AWS Network Firewall

• Databases: Amazon RDS, Amazon Aurora, Amazon DynamoDB, Amazon DocumentDB, Amazon Elasticache, and Amazon MemoryDB

• AI/ML: Amazon Q Business, Amazon Q Developer, Amazon Bedrock, Amazon SageMaker

Microsoft Azure featuring analytics and AI workloads

Microsoft Azure is Microsoft’s enterprise cloud offering and often appeals to organizations with data and analytics needs across their applications. It offers a range of cloud services, including virtual machines, app services, and AI and machine learning. Supported by Microsoft’s extensive data center networks, you can use Azure for general cloud computing, data analytics, application development, and more with a portfolio of over 200 products. It integrates with Microsoft’s existing enterprise software and supports open-source technologies such as Linux, making it a suitable choice for businesses that are deeply entrenched in Microsoft technologies.

Core offerings:

• Compute: Azure VMs, Linux VMs, Azure Compute Fleet, Azure Quantum, Windows Server Azure Containers, and Azure Functions

• Storage: Azure Blob Storage, Azure Data Lake Storage, Azure Backup, Azure Managed Lustre, and Azure Container Storage

• Databases: Azure SQL, Azure PostgreSQL, Azure MySQL, Azure Horizon DB, and Azure Managed Redis

• Networking: Azure NAT Gateway, Azure Virtual WAN, Azure Virtual Network, Azure VPN Gateway, and Azure Application Gateway

• AI/ML: Microsoft Foundry, Azure Machine Learning, Azure AI Bot Service, Azure AI Custom Vision, and Data Science VMs

Google Cloud Platform (GCP) featuring a unified developer experience

GCP is Google’s hyperscaler offering designed for developers who want a wide range of tools with high levels of customization. The portfolio includes over 150 cloud computing, storage, big data, machine learning, and networking services. Its cloud services portfolio is extensive and includes many products that offer high levels of customizability, which can make it appealing if you want granular control over workflows and applications. Google’s cloud offerings also integrate with their pioneering technologies, including Kubernetes, BigQuery, and Gemini AI. The company’s commitment to open source also means you can make use of multiple standards (such as PostgreSQL, Apache, GitLab, Jenkins, OSV, PyTorch, and TensorFlow) across different development areas. Google Cloud support is available with free and paid tiers, but thoroughness and response times depend on the plan you choose and the additional technical assistance you purchase.

Core offerings:

• Compute: Google Compute Engine, Cloud GPUs, Cloud TPUs, Spot VMs, and Deep Learning VM Images

• Storage: Cloud Storage, Filestore, Cloud Storage for Firebase, NetApp Volumes, Persistent Disk, Filestore, and Memorystore

• Databases: Cloud SQL, Spanner, Firestore, AlloyDB, Bigtable, Elastic Cloud, and bare metal Oracle servers

• Networking: Cloud CDN, VPC, Cloud DNS, and Cloud NAT

• AI/ML: Vertex AI, Vertex AI Studio, Gemini Enterprise, Gemini Code Assist, Genkit, Firebase AI Logic client SDKs

Alibaba Cloud featuring APAC-focused deployments

Alibaba Cloud, or Aliyun, is an Asia-Pacific (APAC) focused hyperscaler cloud from Alibaba Group. It operates in 92 availability zones across 29 regions, including Mainland China, Singapore, Thailand, Malaysia, Indonesia, Japan, and South Korea, making it a prominent choice for organizations operating primarily in APAC regions. As a public hyperscaler, Alibaba Cloud provides a comprehensive suite of over 100 cloud services and products that are similar to AWS, Azure, and GCP. It can be more cost-effective in some cases, as it offers pay-as-you-go pricing rather than percentage-based pricing. Companies can also use Alibaba’s AI models (such as Tongyi Qianwen and Ovis-U1) and big data analytics offerings to get real-time usage insights and develop AI workflows on open-source LLMs with limited cost overhead.

Core offerings:

• Compute: Elastic Compute Service (ECS), Elastic GPU Service, ECS Bare Metal Instances, Elastic HPC, containers, serverless workflow, and batch compute

• Storage: Elastic Block Storage, Object Storage Service, File Storage NAS, Cloud Parallel File Storage, and Cloud Backup

• Databases: PolarDB, AparaDB RDS, Tair, Lindorm, Aspara for MongoDB and HBase

• Networking: VPC, NAT Gateway, Network Intelligence Service, Alibaba Cloud DNS PrivateZone, Global Accelerator, and Cloud Enterprise Network

• AI/ML: Alibaba Cloud Model Studio, Platform for AI (PAI), DashVector, AIRec, OpenSearch, AgentBay, Machine Translation, and Intelligent Computing Service PAI-Lingjun

IBM Cloud featuring high-security compliance measures

IBM Cloud is often used in highly regulated industries (such as government and finance) that require a resilient, secure, and compliant cloud, and it provides access to over 230 connected services. It also supports AI workloads at scale with its IBM Spyre accelerator chip and integrates with its Watson technology for AI/ML development. IBM Cloud is designed for hybrid deployments that require a combination of on-premises, SaaS, PaaS, and cloud-native workloads. For security and compliance, IBM provides its own proprietary framework to ensure that data is secure at every lifecycle stage for business applications and generative AI.

Core offerings:

• Compute: Bare metal servers, cloud virtual server, GPUs, IBM Cloud Code Engine, VPS hosting, and virtual servers for VPC

• Storage: IBM Cloud Backup, IBM Cloud Block Storage, IBM Cloud File Storage, and IBM Cloud Object Storage

• Databases: Elasticsearch, EnterpriseDB, etcd, MongoDB, MySQL, PostgreSQL, Redis, IBM Cloudant, and IBM Informix

• Networking: DNS, IBM Cloud Direct Link, and IBM Cloud Internet Services

• AI/ML: InstructLab on IBM Cloud, RedHat OpenShift AI, RHEL AI, IBM Watson Assistant, IBM Watson Discovery, IBM Watson Knowledge Studio, IBM Watson Natural Language Understanding

Hyperscalers vs. developer-focused cloud providers

While hyperscalers such as AWS, Microsoft Azure, and GCP are dominant players in the cloud market, their pricing structure and complex ecosystems can make them a poor fit for developers at digital-native enterprises. Specialty cloud providers can offer several benefits, including:

• Lower costs: For projects with modest workloads, hyperscalers’ extensive resources might be overkill and lead to unnecessary expenses. For those looking for cloud cost optimization, non-hyperscaler cloud providers are often a more cost-effective option.

• Vendor flexibility: Choosing smaller cloud providers can offer flexibility in terms of vendor lock-in. This is especially true if a more specialized provider focuses on using open-source technology and standards for its offerings, rather than proprietary solutions.

• Tailored support: Specialized cloud providers frequently can offer additional support, especially for individuals and smaller businesses. Smaller providers are often more agile and may offer personalized assistance, quicker response and resolution times, and more flexible SLAs.

When to choose a hyperscaler vs a non-hyperscaler cloud

Although hyperscalers offer multiple benefits, they aren’t always the right option for your organization’s workloads or your team. Here are some criteria to consider when evaluating cloud providers:

*Information reflects opinion based solely on publicly available third-party commentary and user experiences shared in public forums. It does not constitute verified facts, comprehensive data, or a definitive assessment of the service.

DigitalOcean for digital-native enterprises and AI startups

DigitalOcean is a specialized cloud provider with powerful, cost-effective computing resources designed for developers at digital-native enterprises and AI startups. Its portfolio includes virtual machines, Managed Kubernetes, cloud storage, networking, and managed databases. Digital-native enterprises can also access the DigitalOcean Gradient™ AI Agentic Cloud for AI development and production workflows. This ecosystem streamlines infrastructure management and supports AI innovation for teams that want to maintain control over their hardware, access reliable infrastructure, and count on predictable pricing. DigitalOcean focuses on the developer community with expansive resources, documentation, and over 8,000 technical tutorials. Developers also get tailored technical support with every DigitalOcean plan (including the Free tier), unlike hyperscaler cloud support offerings that require a higher financial commitment.

Core offerings:

• Compute: Droplets, Optimized Droplets, Kubernetes, Functions, App Platform

• Storage: Spaces Object Storage, Volume Block Storage, Network File Storage

• Databases: Managed databases for MongoDB, Kafka, PostgreSQL, MySQL, Valkey, and OpenSearch

• Networking: VPC, DNS, Partner Network Connect, Reserved IPs

• AI/ML: Gradient AI Inference Cloud, Gradient AI Agentic Cloud

Hyperscaler cloud FAQ

What makes a cloud provider a hyperscaler?

A hyperscaler cloud provider is a company that has a large, extensive data center network that can effectively scale up and down as resource demands increase. These providers have high levels of security, redundancy, and large (100+) product portfolios to support entire mission-critical workloads and ecosystems. Examples include AWS, Microsoft Azure, Google Cloud Platform, Alibaba Cloud, and IBM Cloud.

Which cloud computing providers support scalable applications?

Almost all cloud computing providers support scalable applications. The hyperscale cloud provider you select will depend on your specific application requirements, how quickly and how much you need to scale your applications, your budget, and any technology integrations. Providers such as DigitalOcean offer the flexibility to configure your infrastructure to your exact needs, deploy open source technology, and receive transparent pricing.

Are hyperscalers only for enterprises?

No, hyperscalers are not only for enterprises, but navigating their service offerings and pricing models is often easier for enterprise teams. Depending on your application requirements, regulatory needs, cloud configuration wants, and budget, it might make more sense for you to choose a specialized cloud provider like DigitalOcean.

What is the difference between hyperscale and cloud computing?

The main difference between hyperscale and cloud computing is overall infrastructure scale, service portfolio, automation, and elasticity. Traditional cloud computing provides on-demand computing services just like hyperscalers, but might have a smaller data center footprint or be designed for specialized computing use cases. Deploy a minimal amount of infrastructure for your applications without a large technical or financial commitment to get your workloads up and running with DigitalOcean.

Why are hyperscaler clouds so expensive?

Hyperscaler clouds often use a pay-as-you-go pricing model. However, this applies to multiple integrated services, such as data egress, storage backups, data transfers, and other regular operational tasks. When you multiply these small charges at an enterprise level, they can become significantly more expensive than those of a cloud provider with tiered or bulk pricing models, like DigitalOcean, which offers transparent, usage-based pricing for its users.

DigitalOcean: Your developer-friendly cloud alternative to hyperscalers

DigitalOcean gives developers everything they need to build, deploy, and scale modern applications—without the complexity or frequently unpredictable costs of hyperscalers like AWS, Azure, GCP, Alibaba, or IBM. From virtual machines to fully managed platforms for containers, databases, and AI workloads, DigitalOcean’s cloud computing offerings are designed to be intuitive, flexible, and production-ready. With straightforward, predictable pricing and powerful APIs, you can move from idea to production quickly while staying in control of your infrastructure.

Key features:

• Scalable Droplet (virtual machines) for general compute and custom workloads

• Fully managed Kubernetes, databases, and object storage for production apps

• App Platform for building and deploying applications without managing servers

• GPU-powered infrastructure and AI-ready Droplets for model training and inference

• Managed AI services for building, deploying, and scaling LLM-powered applications

• Global data center regions with built-in networking and security Simple control panel, CLI, API, and Terraform support for automation

• Predictable, transparent pricing with no long-term contracts

Get started with DigitalOcean to build reliable applications, scale with confidence, and spend less time managing infrastructure—and more time shipping code.

DISCLAIMER: Any references to third-party companies, trademarks, or logos in this document are for informational purposes only and do not imply any affiliation with, sponsorship by, or endorsement of those third parties.

All hyperscaler and DigitalOcean product information cited current as of February 2026.