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Building scalable lakehouses on AWS

Discover how Apache Iceberg is redefining modern data engineering. From lakehouse architecture to real-time analytics — see how to build scalable, high-performance data solutions with AWS S3 Tables and Apache Iceberg.

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Agenda

  1. Introduction to Apache Iceberg
  2. How Apache Iceberg is redefining data engineering?
  3. Apache Iceberg in the data lakehouse architecture
  4. AWS S3 Tables with Native Apache Iceberg Support
  5. Use cases: batch, streaming & real-time analytics

Key topics

  • what Apache Iceberg is and why it’s becoming a cornerstone of modern data infrastructure;
  • how Apache Iceberg addresses common challenges like schema evolution, time travel, and real-time data consistency;
  • how Apache Iceberg enables a unified, high-performance lakehouse architecture across batch and streaming data;
  • how AWS S3 Tables deliver scalable, transactional Iceberg tables integrated with Amazon Glue, Amazon Athena, and more;
  • how do Apache Iceberg tables work for fast analytics across diverse data workloads.

Speaker

Kamil Bartosik

Kamil Bartosik

Cloud Data Engineer

He focuses on building scalable, cloud-native solutions and enjoys working with both the infrastructure and data sides of projects. With experience in both cloud engineering and software development, he often contributes to architecture design and helps clients apply best practices in real-world projects.

Apache Iceberg

Apache Iceberg

Open-source table format for large-scale data lakes

Apache Iceberg on AWS revolutionizes the way data lakes are built, offering transactional, scalable, and cost-optimized data lakes. With native support in services like Amazon EMR, Amazon Glue, Amazon Athena, and Amazon Redshift, you get high performance, schema evolution, and multi-format flexibility — all on Amazon S3.

It's how we build modern, efficient lakehouse architectures that grow with your data, without requiring pipeline rewriting.

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