Cloud MigrationIndustry: Multi-Cloud Enterprise 2021

Azure to AWS Data Warehouse & Pipeline Migration

Migrated Azure Synapse and Data Factory workloads to AWS Redshift and Apache Airflow, cutting compute spend by 25% while expanding processing capacity.

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25%

Compute Cost Cut

Direct savings on monthly cloud data warehousing compute expenses

1 Weekend

Migration Cutover Time

Flawless cutover with zero interruption to Monday morning operations

99.9%

Pipeline Reliability

SLA compliance for daily executive reporting deliverables

01 · Challenge

The problem on the ground

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High and unpredictable Azure Synapse compute licensing fees, paired with complex cross-cloud architecture, slowed down query performance and escalated IT operational budgets.

02 · Solution

How we engineered it

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Converted T-SQL scripts to Redshift PostgreSQL-compliant SQL, translated Azure Data Factory pipelines into Python-native Airflow DAGs, and migrated historical data directly to AWS S3 and Redshift.

03 · Architecture

What's running under the hood

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Code Translation: Converted Azure Synapse T-SQL stored procedures and views to AWS Redshift SQL.

Pipeline Modernization: Replaced Azure Data Factory pipelines with open-source Apache Airflow DAGs.

Data Transfer: Leveraged encrypted AWS Snowball / multi-part S3 upload for secure cross-cloud data transfer.

Cost Optimization: Configured AWS Redshift pause/resume and concurrency scaling to minimize idle compute fees.

04 · Results

What changed for the client

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Reduced monthly cloud data warehousing compute spend by 25%.

Accelerated batch processing execution by 30%.

Streamlined operations by standardizing infrastructure on AWS.

Eliminated proprietary vendor lock-in by using open Airflow DAGs.

Technical Q&A

How was a 25% reduction in compute costs achieved during the Azure to AWS migration?

The 25% cost reduction was achieved by moving from Azure Synapse DWUs to AWS Redshift RA3 instances with decoupled compute and storage, alongside right-sizing node clusters and replacing proprietary Azure Data Factory fees with open-source Apache Airflow.

Were T-SQL scripts fully compatible with AWS Redshift?

No, Azure Synapse T-SQL scripts required conversion for Redshift's PostgreSQL-based syntax. Functions, data types, and stored procedure logic were refactored and validated prior to deployment.

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