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aws-lakehouse

Construct and query AWS lakehouses with Apache Iceberg and Amazon Athena.

12|4|Updated Mar 22, 2026
Search Tags:#AWS#Spark#Iceberg#Athena#S3 Tables
One-click install
npx skills add https://github.com/TeiNam/kiro-with-harness --skill aws-lakehouse
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: aws-lakehouse
Source: https://github.com/TeiNam/kiro-with-harness/tree/main/skills/aws-lakehouse
Command: npx skills add https://github.com/TeiNam/kiro-with-harness --skill aws-lakehouse

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps users to build and query S3-based lakehouses using Apache Iceberg and Athena, addressing the challenges of data storage, query performance, and cost management on AWS.

Core Features & Use Cases

  • S3-based Lakehouse Construction: Provides guidance on using S3 Tables for managed storage and self-managed Iceberg for more control.
  • Querying with Athena: Shows how to use Athena for querying Iceberg tables, including performance considerations and compatibility with Iceberg V3.
  • Spark Processing: Offers tips on using Spark with EMR for complex data transformations.
  • Performance Tuning: Covers strategies for optimizing Spark performance, including the use of vectorized accelerators like Comet and Gluten.
  • Use Case: For a company using AWS and needing to analyze large datasets stored on S3, this Skill would help them to choose the right storage and query options for their lakehouse.

Quick Start

To activate the skill for querying your S3-based Iceberg table with Athena, run: 'query_iceberg_table'.

Frequently Asked Questions about aws-lakehouse

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build an AWS lakehouse with S3 Tables and Apache Iceberg?▼

You can build an AWS lakehouse with S3 Tables and Apache Iceberg by using managed S3 Tables for storage or self-managed Iceberg for greater control, combined with Iceberg REST catalogs to maintain table metadata.

How do I query Apache Iceberg tables using Amazon Athena?▼

You can query Apache Iceberg tables using Amazon Athena by running standard SQL queries against your S3-based data source. Athena supports querying Iceberg tables, including compatibility with Iceberg V3, though you should consider specific performance optimizations for large datasets.

What is the best way to optimize Spark performance for Iceberg data transformations on AWS?▼

The best way to optimize Spark performance for Iceberg transformations on AWS is to use Spark with EMR and apply vectorized accelerators like Comet and Gluten. These tools help tune complex data processing and improve query execution speed.

Should I choose S3 Tables or self-managed Iceberg for my AWS lakehouse storage?▼

Choose S3 Tables for managed lakehouse storage to reduce operational overhead, or choose self-managed Iceberg when you need more granular control over your table configurations and metadata management on AWS.

Does Amazon Athena support Iceberg V3 for querying S3 lakehouses?▼

Yes, Amazon Athena supports querying Iceberg V3 tables within your S3 lakehouse. You can use Athena to run analytical queries directly on your Iceberg data while evaluating compatibility and performance considerations for your workloads.

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