GCP vs AWS vs Azure Comparing the Top Cloud Platforms
In this article, we will explore the key details about being a Data Engineer across the three major cloud platforms: Google Cloud Platform (GCP), Amazon Web Services (AWS), and Microsoft Azure. We’ll dive into everything from core responsibilities and necessary skills to the tools and best practices for managing data on GCP, AWS, and Azure.
The cloud computing market is expanding rapidly and is expected to hit $2432.87 billion by 2030. In this large market, three main cloud providers—Amazon Web Services (AWS), Google Cloud Platform(GCP), and Microsoft Azure—hold a total of 64% of the market share. When selecting a cloud provider for hosting a website or application, many users often consider these three major options. Although they may appear similar at first glance, each provider has its own strengths and weaknesses that can significantly affect your costs, user experience, and ease of use. This article will highlight the main differences between AWS, GCP, and Microsoft Azure, and explain why you might also want to look at other options like DigitalOcean to help you make a better choice for your cloud provider.
AWS, Azure, and GCP are the top cloud service providers right now, but they each have unique features and histories. Let’s look at some key details about each one before we explore their differences.
Amazon Web Services (AWS): is the cloud infrastructure division of Amazon. It was founded in 2006 and has grown to be the world’s top cloud provider, with a 32% market share in the first quarter of 2023. AWS provides a variety of services like computing, storage, networking, databases, analytics, machine learning, and artificial intelligence. It is utilised by many types of businesses, from small firms to large organisations.
Microsoft Azure was introduced in 2010 and is now the second-largest cloud provider in the world, capturing 23% of the market in the first quarter of 2023. It has a broad range of services, similar to AWS, but is especially designed for Windows-based computing and integrates effectively with other Microsoft offerings.
Google Cloud Platform (GCP): began in 2011 and is now the third-largest cloud provider globally, holding a 9% market share as of Q1 2023. GCP provides many services like AWS and Azure, but it has fewer data centres compared to them. It also offers solutions that are user-friendly for DevOps.
What exactly is cloud computing?
Cloud Computing is about keeping and using data and programs on remote servers available on the internet, rather than on your computer’s hard drive or a local server. It is also known as Internet-based computing, where resources are offered as a service through the internet. You can store various types of data, including files, images, and documents.
Here are some tasks you can do with Cloud Computing:
– Store, back up, and recover data
– Access software as needed
– Create new applications and services
– Stream videos and audio.
Benefits of cloud computing
The cloud gives multiple choices for data storage, serving, and processing. It powers services like Netflix and the Indian Premier League, as well as IoT sensors and machine learning tools. Cloud computing offers several advantages.
Decreased CapEx
Cloud computing changes big upfront costs for infrastructure into smaller, flexible costs that grow with your business. With the cloud, companies don’t have to buy servers and IT gear weeks or months ahead of time. They can quickly set up hundreds or thousands of servers in just minutes and get results more quickly.
Reduced infrastructure maintenance
Cloud computing eliminates the need for physical storage and upkeep, letting IT workers concentrate on important business objectives. Resources are shared to serve multiple users at the same time, offering flexibility in location.
Increased availability
Cloud computing makes IT resources easily accessible with just a click or tap. This quick access cuts down the time developers need to get these resources from weeks to just minutes. The lower costs and faster experimentation help organisations become more agile.
Scalability
One of the key benefits of cloud computing services is their ability to scale up or down as needed. This feature helps organisations be more agile by allowing them to access necessary resources like bandwidth, storage, and computing power. Users can obtain IT resources in the cloud at the right time and from the most suitable location.
Selecting a cloud service provider is a big decision for any organisation. Consider these important factors when making your choice.
Service Offerings: Check the variety of services each provider has and see how they fit your needs. Look at options like computing, storage, networking, databases, AI/ML, IoT, analytics, and other specialised services.
Scalability: Make sure the provider can handle your current and future growth needs. The ability to adjust resources based on demand is important for many businesses.
Performance and Reliability: Investigate the provider’s history of uptime and reliability. Look for backup systems and failover options to reduce downtime.
Security: Review the provider’s security practices, such as data encryption, compliance certifications, access controls, and monitoring. Make sure they follow your security and compliance rules.
Cost: Compare pricing models, including pay-as-you-go and reserved instances, discounts, and any hidden fees. Think about your budget and expected usage to find the best value.
Support and SLAs: Examine the provider’s support services, response times, and service level agreements (SLAs). Ensure they provide enough support for your needs, especially for critical tasks.
Geographic Presence: Look at the provider’s global reach and availability zones. Choose one with data centres in locations that suit your business needs for latency, data sovereignty, and disaster recovery.
Integration and Compatibility: Evaluate how well the provider’s services work with your current systems, tools, and workflows. Compatibility with third-party software and open standards is key for smooth integration.
Community and Ecosystem: Research the provider’s developer community, documentation, and network of partners and third-party tools. A strong ecosystem can offer extra resources, support, and chances for innovation.
Regions and availability
When choosing a cloud provider, the first things to think about are the supported regions and availability. Factors like latency and compliance rules can greatly affect your cloud performance, especially when handling data.
Data directly affects how well your cloud performs.
Here are the Big Three as of March 2023:
Amazon Web Services has a presence in 30 regions worldwide, with two located in India (Mumbai and Hyderabad). It features 96 availability zones and over 410 Points of Presence.
Microsoft Azure is available in 54 regions, including multiple locations in India such as Pune, Chennai, Mumbai, and a future site in Hyderabad. Each region has at least three availability zones and 116 edge locations.
Google Cloud Platform operates in 35 regions, which includes the Delhi National Capital Region. It has 106 zones and more than 200 edge locations.
Easy to Navigate : AWS has a user-friendly interface that makes it easier for users to explore and utilise its vast array of services. The AWS Management Console provides intuitive navigation, allowing users to quickly access tools and resources.
Many Tools to Choose From : AWS offers a comprehensive suite of tools and services, ranging from compute and storage to machine learning and analytics. This extensive selection allows businesses to tailor solutions to their specific needs, enabling innovation and efficiency.
Unlimited Server Options : AWS provides virtually unlimited server capacity with its Elastic Compute Cloud (EC2) service, allowing businesses to scale up or down based on demand. This flexibility ensures that companies can handle fluctuating workloads without disruption.
Amazon EC2 Constraints : While AWS offers powerful EC2 instances, there can be limitations in terms of instance types and regional availability. Some users may find these constraints challenging when seeking specific configurations or working in less-served regions.
Cons :
Amazon EC2 Limitations : Despite the flexibility of EC2, users may encounter limitations in terms of instance types, pricing models, or availability in certain regions. These constraints can impact the ability to optimise performance and cost-effectiveness for specific workloads.
Security Weaknesses : AWS provides robust security tools, but the shared responsibility model places some security responsibilities on the customer. Misconfigurations or inadequate security practices on the user’s end can lead to vulnerabilities, potentially exposing sensitive data.
Microsoft Azure :
Pros :
Data Security : Azure offers strong security features, including advanced threat protection and compliance with major industry standards. Its extensive security certifications and built-in tools help protect data and ensure regulatory compliance.
Cost-Effective : Azure provides flexible pricing options and various cost-saving features, such as reserved instances and autoscaling. This can lead to significant savings, especially when optimising resource usage based on demand.
App-friendly : Azure is designed to support a wide range of applications and development frameworks. Its integration with Microsoft technologies and tools enhances the development, deployment, and management of applications, making it a preferred choice for developers.
Scalable : Azure offers robust scalability options, allowing businesses to easily scale resources up or down based on their needs. This elasticity ensures that applications can handle varying workloads efficiently without performance issues.
Cons :
Requires Management : While Azure offers extensive features, effective management of resources and services requires ongoing oversight. Users must actively monitor and configure settings to optimise performance and cost.
Requires Platform Expertise : Azure’s vast array of services and capabilities necessitates a certain level of expertise. Organisations may need to invest in training or hire specialists to fully leverage Azure’s features and ensure efficient use.
Difficult Migration : Migrating existing applications and data to Azure can be complex and time-consuming. Organisations may face challenges in adapting their systems to the Azure environment, which can lead to extended migration timelines and potential disruptions.
Google Cloud Platform :
Pros :
G-Suite : GCP offers seamless integration with Google Workspace (formerly G-Suite), enhancing productivity with tools like Gmail, Google Drive, and Google Meet. This integration allows for smooth collaboration and data sharing across platforms.
Insights from AI: GCP leverages advanced AI and machine learning capabilities, providing powerful tools for data analysis and insights. Services like BigQuery and AutoML enable businesses to derive valuable insights and make data-driven decisions efficiently.
Highly Secure: GCP is known for its strong security measures, including encryption, identity and access management, and compliance with major industry standards. Its security infrastructure helps protect data and safeguard against potential threats.
Cons :
Poor documentation : Some users find that GCP’s documentation can be lacking in detail or clarity, making it challenging to understand and implement certain features. This can slow down development and troubleshooting processes.
Need Management : Effective use of GCP requires active management of resources and configurations. Without proper oversight, users may encounter issues related to performance, cost, or security, necessitating ongoing attention and adjustment.
Hybrid and multi-cloud options
Many businesses find that the best cloud solution is a mix of public and private clouds. A hybrid cloud lets you use one or more public clouds alongside your current infrastructure and a private cloud. This combination allows you to run applications in different environments, making it a favoured choice for companies that have already spent a lot on their IT systems.
By using a blend of computing, storage, and service environments (like on-premises infrastructure, private cloud services, and public cloud), an organisation can gain significant advantages. The hybrid cloud ensures clear coordination among these different platforms.
Small Instance (2 vCPUs, 8 GB RAM): Approximately $69/month.
Large Instance (3.84 TB RAM, 128 vCPUs): About $3.97/hour.
Azure:
Small Instance: Approximately $70/month.
Large Instance (3.89 TB RAM, 128 vCPUs): About $6.79/hour.
GCP:
Small Instance: Approximately $52/month (25% cheaper than AWS).
Large Instance (3.75 TB RAM, 160 vCPUs): About $5.32/hour.
Storage Charges:
AWS:
• SSD 128GB: $12 monthly.
• Object Storage (500 GB): $13 monthly.
Azure:
• SSD 128GB: $11 monthly.
• Object Storage (500 GB): $13 monthly.
GCP:
• SSD 128GB: $15 monthly.
• Object Storage (500 GB): $12 monthly.
Discounts and Pricing Options :
AWS: Provides Reserved Instances (RIs) that can save you up to 75% if you commit long-term.
Azure: Offers Reserved Instances with discounts reaching 72% and works seamlessly with Microsoft services.
GCP: Has Committed Use Discounts (CUD) and Sustained Use Discounts, allowing savings without needing upfront commitments.
Market shares
Check the market shares to see which is better: AWS, Azure, or Google Cloud. In the cloud market, AWS is currently in the top position. For more details, look at the image below.
AWS holds the top position with about 32% of the market share.
Microsoft Azure follows in second place with around 22%.
Google Cloud is in third place, having nearly 11% of the market share.
Public Cloud Adoption for Enterprises
In the race for public cloud usage, Azure is in first place, while AWS and Google Cloud take the second and third spots. Choosing Azure for your business can provide advantages like improved data storage, computing power, networking, and additional benefits.
Among the enterprises surveyed
76% are utilising AWS 69% are utilising Azure and 34% are utilising Google
Predictions show that the global cloud discovery market will experience fast growth, with a compound annual growth rate of 16.2 percent projected from 2023 to 2033. Although a recession could slow this growth, it won’t stop it entirely. There is a strong demand for programmers and developers now and in the future. Learning a programming language will make you more attractive to potential employers.
Salaries for AWS Cloud Developers vary significantly based on experience levels. Here’s a breakdown of the average salaries for entry-level, mid-level, and expert-level AWS Cloud Developers:
Entry-Level AWS Cloud Developer
India: Approximately ₹3,20,000 to ₹3,50,000 per annum.
USA: Around $85,866 to $114,194 per year.
Mid-Level AWS Cloud Developer
India: Approximately ₹5,80,000 to ₹5,90,000 per annum.
USA: Typically around $99,293 to $102,255 per year.
Expert-Level AWS Cloud Developer
India: Salaries can reach up to ₹13,60,000 per annum.
USA: Expert-level positions, such as AWS Certified Solutions Architect – Professional, can command salaries around $142,000 annually.
These figures illustrate the potential earnings for AWS Cloud Developers, reflecting the demand for cloud computing skills in the job market.
Salaries for Azure Cloud Developers can vary significantly based on experience levels. Here’s a summary of the average salaries for entry-level, mid-level, and expert-level Azure Cloud Developers:
Entry-Level Azure Cloud Developer
India: Approximately ₹3.9 to ₹5.0 lakhs per year.
USA: Around $50,000 to $97,000 per year.
Mid-Level Azure Cloud Developer
India: Approximately ₹7.0 to ₹12.0 lakhs per year.
USA: Typically around $100,000 to $132,148 per year.
Expert-Level Azure Cloud Developer
India: Salaries can reach up to ₹25 lakhs per year.
USA: Expert-level positions can command salaries around $132,148 to $140,000 annually.
These figures reflect the demand for Azure skills in the job market, with higher salaries for those with more experience and specialised skills in cloud technologies.
Salaries for Google Cloud Platform (GCP) Developers vary based on experience levels. Here’s a summary of the average salaries for entry-level, mid-level, and expert-level GCP Developers:
Entry-Level GCP Developer
USA: Approximately $86,053 annually.
India: Salaries typically range from ₹1.6 lakhs to ₹5 lakhs per year.
Mid-Level GCP Developer
USA: Generally around $105,000 to $120,000 per year.
India: Salaries can range from ₹6 lakhs to ₹14.5 lakhs annually, depending on experience and skills.
Expert-Level GCP Developer
USA: Expert positions can command salaries around $130,000 to $160,000 annually.
India: Salaries for experienced professionals can reach up to ₹20 lakhs or more per year.
These figures highlight the demand for GCP skills in the job market, with higher salaries for those with more experience and specialised expertise in cloud technologies.
Famous Brands Using Them
AWS stands out as a key player in the cloud market, enjoying robust community support and a vast user base. It serves many prominent brands globally, such as Netflix, Airbnb, Unilever, BMW, Samsung, MI, Zynga, Twitch, LinkedIn, Facebook, Baidu, and ESPN. ValueCoders has also developed several applications using AWS technology, including the Church App and an Online Food Ordering Hub.
Azure has gained a strong reputation, with around 80% of Fortune 500 companies as its clients. Some notable brands using Azure are eBay, Boeing, Samsung, HP, Polycom, GE Healthcare, Johnson Controls, BMW, Travelocity, Fujifilm, Honeywell, and Apple.
Google being a leading brand, provides Google Cloud and Google App Engine services, which are used by clients like HSBC, Vimeo, Twitter, PayPal, Snapchat, 20th Century Fox, BestBuy, Bloomberg, and Domino’s.
When comparing AWS, Google Cloud Platform (GCP), and Azure, consider the unique use cases and target groups for each option. Each cloud provider offers different benefits, and certain businesses or sectors might lean towards one based on their specific needs.
AWS (Amazon Web Services) :
Use Cases:
Enterprise Applications: AWS is a popular choice for large companies that need flexible infrastructure, strong data storage, and various services to run and manage their applications.
E-commerce: AWS is ideal for busy online stores, using services like AWS Lambda, EC2, and RDS to ensure they can handle lots of traffic reliably.
Big Data and Analytics: AWS has tools such as Amazon Redshift, Athena, and EMR for processing, analysing, and storing large amounts of data.
Machine Learning and AI: Amazon SageMaker offers a service to help create, train, and launch machine learning models easily
Disaster Recovery: With its worldwide network, AWS helps businesses create effective disaster recovery plans with little downtime.
Target Audiences:
Large Companies: AWS is perfect for big organisations that require a wide variety of services and a global presence.
New Businesses: The AWS Activate program offers startups credits and resources to help them grow and develop.
Tech Experts: AWS has a lot of documentation, APIs, and a strong community, making it a favourite among developers and IT professionals.
Regulated Sectors: With many compliance certifications, AWS is a good fit for industries such as finance, healthcare, and government.
Google Cloud Platform (GCP) :
Use Cases:
1. Data Analytics and Big Data: GCP is well-known for its strong data analytics tools like BigQuery, Dataflow, and Dataproc, which excel in processing and analysing large datasets.
Machine Learning and AI: GCP provides powerful machine learning options, including TensorFlow, AutoML, and Vertex AI, making it ideal for AI-focused projects.
DevOps and CI/CD: GCP works well with Kubernetes (GKE) and has various tools for continuous integration and delivery, such as Cloud Build and Cloud Deployment Manager.
Media and Entertainment: GCP’s robust infrastructure supports media streaming, content delivery, and rendering tasks thanks to its high-performance networking and storage.
Hybrid and Multi-cloud Strategies: With Anthos, GCP helps businesses manage workloads across different cloud environments.
Target Audiences:
Data Scientists and Analysts: GCP is a top choice for those working in data analytics, big data, and machine learning.
Startups and Tech Companies: Businesses aiming to use advanced AI/ML technologies often select GCP.
Educational Institutions and Researchers: GCP provides credits and resources to assist educational and research projects.
Media Companies: GCP’s services are designed to meet the needs of content creators and distributors.
Azure :
Use Cases:
Enterprise IT and Hybrid Cloud: Azure works well with Microsoft products, making it ideal for businesses using Windows Server, Active Directory, or other Microsoft tools.
Application Development: Azure supports various app development with tools like Visual Studio, Azure DevOps, and Azure App Service.
IoT Solutions: Azure IoT Hub and Azure Digital Twins help companies create and manage IoT solutions.
AI and Machine Learning: Azure provides AI services such as Azure Machine Learning and Cognitive Services for smart app development.
SAP on Azure: Many companies choose Azure for SAP workloads because of its optimised setup and partnership with SAP.
Target Audiences:
Large Enterprises: Especially those already using Microsoft products, as Azure fits well into Microsoft’s ecosystem.
Developers: Azure offers a wide range of development tools, making it suitable for those creating enterprise applications.
Government and Public Sector: Azure has strong security and compliance features for government needs.
Manufacturing and Industry: Azure’s IoT and AI features are perfect for industries focused on automation.
AWS, Google Cloud Platform (GCP), and Azure each offer strong cloud services tailored to diverse industries such as retail, healthcare, and finance. When comparing GCP vs AWS vs Azure, AWS is known for its extensive service range and scalability, making it a top choice for both large enterprises and startups. GCP stands out for its advanced data analytics and machine learning capabilities, appealing to tech-focused businesses that prioritize innovation. Azure, on the other hand, is favored by organizations already using Microsoft products, making it particularly suited for sectors like manufacturing and government.
Selecting the right cloud provider—whether AWS for scalability, GCP for data analysis, or Azure for seamless enterprise integration—depends on a business’s specific needs, industry requirements, and existing technology stack. Each platform offers unique benefits that can help businesses grow and innovate. By leveraging the strengths of these cloud services, companies can enhance efficiency, drive digital transformation, and stay competitive in a rapidly evolving market.
AWS is known for its extensive range of services and global infrastructure. GCP excels in data analytics, machine learning, and AI capabilities. Azure integrates seamlessly with Microsoft products and is popular for enterprise solutions and hybrid cloud environments
Cost-effectiveness depends on specific use cases, service requirements, and usage patterns. AWS, GCP, and Azure all offer competitive pricing, with various discounts and savings plans. GCP often highlights its sustained-use discounts, while AWS and Azure offer reserved instance pricing for long-term commitments.
All three cloud providers offer startup programs with credits and resources. AWS Activate, Google Cloud for Startups, and Microsoft for Startups each provide support, but the best choice depends on the startup’s technology stack, budget, and growth plans.
All three platforms provide strong security features, including encryption, identity and access management, and compliance with major industry standards. AWS has a vast suite of security tools, GCP emphasises secure defaults and data protection, and Azure offers deep integration with enterprise security frameworks.
Yes, this is known as a multi-cloud strategy. Many organisations use services from multiple cloud providers to leverage the strengths of each platform, avoid vendor lock-in, and increase redundancy and flexibility.
Consider factors such as your existing technology stack, specific service needs, budget, geographic requirements, and long-term business goals. AWS is ideal for broad use cases, GCP for data and AI, and Azure for Microsoft integration.
All three cloud providers offer robust disaster recovery solutions. AWS provides services like AWS Backup and AWS Disaster Recovery. GCP offers tools like Cloud Storage and Persistent Disk snapshots. Azure provides Azure Site Recovery and Azure Backup for DR needs.
