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Presenting at DataEngBytes 2024 Sydney: Building a Transactional Data Lakehouse on AWS with Apache Iceberg
- Building a Transactional Data Lakehouse on AWS with Apache Iceberg was discussed at DataEngBytes 2024 Sydney. A data lakehouse architecture delivers a unified platform that supports both analytical and transactional workloads for managing structured, semi-structured, and unstructured data at scale.
- Apache Iceberg is an open table format that manages large-scale, transactional data in data lake environments. It supports ACID compliance for data consistency and reliability and gracefully handles schema changes, along with partitioning and performance optimization.
- Iceberg tables are stored in Amazon S3, and AWS Glue allows serverless ETL processing of data into Iceberg tables, making it possible to handle batch and real-time updates. Athena supports SQL queries on Iceberg tables directly from S3, making it easy to query and analyze data without dedicated infrastructure.
- A data lakehouse with Iceberg allows for real-time analytics with consistent, ACID-compliant data, historical data access through time travel for auditing and compliance, and cost efficiency by storing data in S3 and using Athena for on-demand queries.
- The architectural overview of building a lakehouse on AWS with Iceberg consists of an ingestion layer, storage layer, processing layer, query layer, and governance layer, ensuring scalability, cost-effectiveness, and data consistency.
- Efficient partitioning, schema evolution, cost management, and data governance are essential lessons for working with Iceberg on AWS. Planning for data distribution patterns, backward compatibility, and fine-grained access control will prevent breaking data pipelines and ensure data security.
- Designing Iceberg tables with strong partitioning strategies, leveraging Lake Formation, using time travel features and efficiently scheduling Glue jobs to process incremental updates can optimize data modeling, governance, and compliance for building a data lakehouse with Iceberg on AWS.
- A transactional lakehouse architecture with Iceberg on AWS unlocks new possibilities for data-driven organizations seeking both performance and data governance.
- Apache Iceberg and AWS's scalability can adapt to evolving data needs while ensuring reliability and governance, making it a powerful foundation for a data lakehouse approach.
- If you're exploring a lakehouse approach, considering Apache Iceberg and AWS would be a great start to building a scalable, cost-effective, and resilient data solution.
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