Google Cloud Platform (GCP) and Amazon Web Services (AWS) are both popular cloud computing platforms that offer a wide range of services for businesses and organizations. Both GCP and AWS provide infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS) offerings, allowing customers to build, deploy and run applications in the cloud.
Here are some key differences between GCP and AWS:
- Services: GCP and AWS offer a similar set of services, but they may have different names and slightly different functionality. GCP has a strong focus on big data and machine learning, while AWS has a wider range of services and a more established ecosystem of partners and third-party tools.
- Pricing: GCP and AWS have different pricing models, with GCP generally being more flexible and customizable, while AWS often has a more straightforward pricing structure. GCP also offers sustained-use discounts, which can lower the cost of running long-running workloads.
- Networking: GCP has a strong emphasis on global networking and offers services such as Google's global load balancer and Cloud VPN, while AWS has a more established ecosystem of partners and third-party tools for networking.
- Data and Analytics: AWS has a wide range of data and analytics services, including Redshift, RDS, and Elasticsearch, while GCP has a big data focus with services such as BigQuery and Cloud Dataflow.
- Machine learning: GCP has a strong focus on machine learning, with services such as TensorFlow, Cloud ML Engine, and Cloud Vision API, while AWS also has a range of machine learning services including SageMaker, Rekognition, and Lex.
- Support: AWS has a more established support system with different levels of support options and a larger community, while GCP has a more limited support system and a smaller community.
GCP over AWS and Vice-Versa?
Choosing between Google Cloud Platform (GCP) and Amazon Web Services (AWS) can depend on several factors, including the specific services and features offered by each platform, the pricing model, and the overall fit with your organization's existing infrastructure and workflow.
Here are some factors to consider when deciding between GCP and AWS:
- Services: If your organization has specific needs for big data and machine learning, GCP may be a better choice as it has a strong focus on these areas. On the other hand, if your organization requires a wide range of services and a more established ecosystem of partners and third-party tools, AWS may be a better choice.
- Pricing: GCP offers more flexible and customizable pricing, while AWS often has a more straightforward pricing structure. GCP also offers sustained-use discounts, which can lower the cost of running long-running workloads.
- Networking: GCP has a strong emphasis on global networking, with services such as Google's global load balancer and Cloud VPN, while AWS has a more established ecosystem of partners and third-party tools for networking.
- Data and Analytics: If your organization has a need for data warehousing and business intelligence, AWS has a wide range of services like Redshift, RDS, Elasticsearch, and more, while GCP has a big data focus with services such as BigQuery and Cloud Dataflow.
- Machine learning: GCP has a strong focus on machine learning, with services such as TensorFlow, Cloud ML Engine, and Cloud Vision API, while AWS also has a range of machine learning services including SageMaker, Rekognition, and Lex.
- Support: If your organization requires a more established support system with different levels of support options and a larger community, AWS may be a better choice. GCP has a more limited support system and a smaller community.
- Hybrid and Multi-cloud: If your organization is planning to adopt a multi-cloud strategy, AWS has a more mature offering for hybrid and multi-cloud scenarios, with services such as Outposts and App Runner
Service Level Agreement (SLA)
They both offer a wide range of services with different Service Level Agreements (SLAs).
AWS offers an SLA of 99.95% availability for its Elastic Compute Cloud (EC2) and Elastic Block Store (EBS) services. Additionally, it offers an SLA of 99.99% for its Amazon RDS, Amazon DynamoDB, and Amazon ElastiCache services.
GCP offers a similar level of availability for its Compute Engine and Persistent Disk services, with an SLA of 99.95%. GCP also offers an SLA of 99.99% for its Cloud SQL and Cloud Datastore services.
When it comes to SLA, both AWS and GCP offer very similar levels of availability for their core services. However, AWS has a slightly higher SLA for some of its services than GCP.
It's also important to note that, while SLA is an important factor to consider when choosing a cloud provider, it's not the only one. Other factors such as security, scalability, and pricing should also be taken into account.
It's always a good idea to thoroughly review the SLA and other details of the services you plan to use with each provider before making a decision, as well as regularly monitor the services to ensure they meet their SLA.
AWS or GCP, Who has better availability region wise
Both AWS and GCP have a global presence, with multiple data centers and availability regions around the world.
AWS currently has 77 availability regions worldwide and plans to have 84 by the end of 2022. These regions are spread across 24 countries and are designed to provide low latency and high availability for customers.
GCP has 35 regions worldwide and it is spread across 14 countries. It also has plans to expand to more regions in the future and will have a total of 44 regions available by the end of 2024.
In terms of region coverage, AWS has more availability regions than GCP. However, it's important to note that the number of regions doesn't necessarily translate to better availability. The availability of service also depends on factors such as network infrastructure, data center design, and disaster recovery capabilities.
The most popular service of AWS and GCP is based on different regions there are other factors such as industry type or use-case that service is more popular but today we will see only region based
- In North America, AWS's Elastic Compute Cloud (EC2) and Simple Storage Service (S3) are among the most popular services. EC2 is widely used for hosting web applications, running big data workloads, and more, while S3 is popular for storing and retrieving files, images, and backups.
- In Europe, AWS's Elastic Container Service (ECS) and Elastic Container Registry (ECR) are also popular among users. ECS allows users to easily manage and run containerized applications, while ECR is a fully-managed Docker container registry that makes it easy to store, manage, and deploy Docker container images.
- In Asia, AWS Elastic Block Store (EBS) and Amazon Relational Database Service (RDS) are among the most popular services. EBS provides block-level storage for use with EC2 instances, while RDS provides a managed relational database service for use with databases such as MySQL, PostgreSQL, and Oracle.
- As for GCP, In North America, Google Compute Engine (GCE) and Google Cloud Storage (GCS) are among the most popular services. GCE allows users to launch virtual machines and configure network and security settings, while GCS is an object storage service that allows users to store and retrieve large amounts of data in the cloud.
- In Europe, GCP's BigQuery and Cloud SQL are popular among users. BigQuery is a fully managed, cloud-native data warehouse that enables super-fast SQL queries using the processing power of Google's infrastructure, while Cloud SQL is a fully-managed database service for MySQL, PostgreSQL, and SQL Server.
- In Asia, GCP's Cloud Spanner and Cloud Translation API are also popular among users. Cloud Spanner is a fully-managed, horizontally scalable, relational database service, while Cloud Translation API allows developers to easily translate text between thousands of language pairs.
