Building unified data pipelines with Apache Iceberg and Apache Flink

This article explains how to build unified data pipelines using Apache Iceberg and Amazon Managed Service for Apache Flink, eliminating the need for separate streaming and batch pipelines.

• Dual-pipeline approach doubles infrastructure costs, creates data synchronization issues, and increases operational complexity
• Apache Iceberg's snapshot-based architecture enables incremental streaming without separate pipelines
• Solution uses Amazon S3, AWS Glue Data Catalog, Apache Iceberg, and Amazon Managed Service for Apache Flink
• Requires 11 JAR dependencies for Flink, Iceberg, Hadoop, and AWS SDK integration
• Includes Python implementation with environment setup, catalog configuration, and streaming logic
• Production deployment requires performance tuning, monitoring, cost management, and security controls
• Checkpoint intervals, partition pruning, and parallelism settings optimize performance and cost
• Security best practices include least-privilege IAM roles, KMS encryption, and VPC endpoints
• Estimated cost: $5-10 for 2-hour walkthrough; $0.11/hour per KPU for production runtime

This guide provides a complete technical walkthrough for replacing dual pipelines with a single unified system handling both real-time and batch access from the same data layer.