Automated Data Lake Architecture with Apache Hudi
Developed a scalable Data Lake on AWS to process high-frequency Change Data Capture (CDC) logs from MS SQL Server into a transactional storage layer.
Transactional Data Lake Architecture
MS SQL Server → DMS → S3 Raw → Glue (with DynamoDB Checkpointing) → Apache Hudi → Athena → QuickSight
How It Works
End-to-end transactional data lake with incremental processing
CDC Data Capture
AWS DMS captures real-time changes from MS SQL Server using Change Data Capture (CDC). Full load and incremental change files are continuously written to the S3 Raw landing zone.
Scheduled Orchestration
Amazon EventBridge runs a daily cron job that triggers AWS Step Functions. The workflow orchestrates the entire ETL pipeline based on custom configuration parameters.
Checkpoint-Based Processing
The Glue job queries DynamoDB to retrieve the last successful run timestamp for each table. This checkpoint system ensures only new/changed files (incremental loads) are processed from the raw S3 bucket.
Glue ETL with PySpark
AWS Glue jobs read incremental data from S3 Raw, apply business transformations, and implement SCD Type 1 (overwrite) and Type 2 (historical tracking) logic before writing to Apache Hudi.
Apache Hudi Transactional Lake
Apache Hudi provides ACID transactions on S3, enabling reliable upserts, deletes, and complex data mutations. Copy-on-Write (COW) tables optimize read performance for analytics workloads.
Analytics & Reporting
Amazon Athena queries the Hudi tables directly using SQL, enabling stakeholders to run ad-hoc analytics. QuickSight connects to Athena for interactive dashboards and business intelligence.
Key Features
ACID Transactions
Apache Hudi provides ACID compliance on S3, enabling reliable data updates with transaction guarantees and rollback capabilities.
SCD Type 1 & Type 2
Implements both overwrite (Type 1) and historical tracking (Type 2) patterns for comprehensive slowly changing dimension management.
Checkpoint System
DynamoDB-based checkpointing tracks last successful run per table, ensuring exactly-once processing of incremental data.
Incremental Processing
Process only new/changed files since last checkpoint, dramatically reducing processing time and compute costs.
Serverless Orchestration
EventBridge and Step Functions provide fully managed scheduling and workflow orchestration without infrastructure management.
Analytics Ready
Optimized Hudi COW tables enable high-performance SQL queries via Athena for real-time analytics and reporting.
Build Your Transactional Data Lake?
Let's discuss how Apache Hudi and AWS can transform your data architecture with ACID guarantees.
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