GCP to AWS Data Engineering Bridge
Translate your existing knowledge of BigQuery, GCS, Pub/Sub, Composer, and Service Accounts directly into Amazon Redshift, Athena, S3, Kinesis, MWAA, and AWS IAM.
Data Engineering Translation Tracks
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Data Lake & Object Storage
From Google Cloud Storage (GCS) to Amazon Simple Storage Service (S3).
GCS and S3 are conceptual siblings! Both are flat object stores with 11 Nines durability where slashes represent key prefixes. The key differences in AWS are: 1) S3 has many more specialized storage tiers (including Intelligent-Tiering and Glacier Deep Archive), and 2) S3 security is controlled via two distinct layers: IAM User Policies AND S3 Bucket Resource Policies.
Data Warehousing & SQL Analytics
From BigQuery dynamic Dremel slots to Amazon Redshift MPP (Distkeys/Sortkeys) & Amazon Athena.
If you want BigQuery's exact serverless pay-per-query experience in AWS, use **Amazon Athena** ($5.00/TB scanned over S3 Parquet with zero cluster setup). If you want an enterprise provisioned data warehouse with dedicated high-concurrency throughput, use **Amazon Redshift** where you explicitly declare `DISTKEY` (sharding) and `SORTKEY` (clustering)!
Real-Time Streaming & Message Ingestion
From Pub/Sub per-message ACK model to Amazon Kinesis Data Streams (Shards & Offsets).
In GCP Pub/Sub, you don't manage partitions, and messages disappear when ACKed. In Amazon Kinesis Data Streams, you manage Shards (or use Kinesis On-Demand mode), messages are immutable logs retained for up to 365 days, and consumer worker applications maintain their own sequence number checkpoints in DynamoDB.
Pipeline Orchestration & Workflow DAGs
From Cloud Composer (Managed Airflow on GKE) to Amazon MWAA (Managed Airflow on AWS) & AWS Step Functions.
If you want to keep your Python Apache Airflow DAGs, **Amazon MWAA (Managed Workflows for Apache Airflow)** is the exact 1-to-1 equivalent to Cloud Composer! If you want a 100% serverless, zero-maintenance orchestrator with visual execution graphs, use **AWS Step Functions**.
Service Accounts, IAM & Local App Access
From GCP Service Accounts & JSON Keys to AWS IAM Users, Access Keys, Roles & Boto3 Credential Chains.
In GCP, you create a 'Service Account' and download a JSON key file. In AWS, you create an 'IAM User' and generate an 'Access Key ID & Secret Access Key' (or assume an IAM Role). In Python, Boto3 automatically checks environment variables and local `~/.aws/credentials` with the exact same convenience as Google's ADC!