Explore the basic technologies in public cloud platform: Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP).
Compute
#- At on-prem, or traditional data center, Compute is referring to the physical server.
- At cloud, Compute is referring to
virtual machine or container or serverless. - typically,
virtual machine isn’t the go-to technology to use nowadays. serverless solution is easier to be used (called endpoint).
| Compute Technologies | AWS | Azure | GCP |
|---|
| Serverless | Lambda | Azure Functions | Google Cloud Functions |
| Virtual Machine | EC2 | Virtual Machine | Compute Engine |
| Hosted Container | Fargate | Container Instances | Cloud Run |
| Container Orchestration | EKS | AKS | Kubernetes Engine |
Storage
#- For storing data as object.
- Can apply labels and filters to the object.
- typically used for long-term storage, like PDF and word files (unstructure data).
| Object Storage | AWS | Azure | GCP |
|---|
| Storage | S3 | Blob Storage | Cloud Storage |
Database
#- For structure data which allows for querying and complex transaction.
- Optimized for frequent access.
- More specialized DB such as knowledge graphs, vector DB.
| Database | AWS | Azure | GCP |
|---|
| Relational DB | MySQL/PostgreSQL | MySQL/PostgreSQL | MySQL/PostgreSQL |
| NoSQL | DynamoDB | CosmosDB | Firestore/datastore |
| Data warehouse | RedShift | Synapse Analytics | BigQuery |
AL/ML
#- Solutions for vision-focused, generative AI, etc.
- Still new.
| AI/ML | AWS | Azure | GCP |
|---|
| Pre-built AI | Amazon Rekognition, Amazon Translate, Amazon Comprehend | Azure Cognitive, Azure Machine Learning | Google Cloud Vision AI, Google Cloud Translation, Google Cloud Natural Language |
| ML | SageMaker | Azure Machine Learning | Vertext AI |
| AutoML Tools | SageMaker Autopilot, Amazon Kendra | Azure Automated ML | AutoML Vision, AutoML Natural Language |
