PyIceberg

Lakevision is a tool which provides insights into your Apache Iceberg based Data Lakehouse.

Sample code to collect Apache Iceberg metrics for table monitoring

A poc open framework to manage data ingestion into apache iceberg tables

Official companion repository for the "Unleash the power of Apache Iceberg on AWS" Book. Includes code samples, deployment guides, ETL examples, and best practices for implementing scalable Apache Iceberg lakehouses on AWS.

Tansu schema-backed topics, instantly accessible as Apache Iceberg tables with pyiceberg

Model Context Protocol (MCP) server for Apache Polaris. Enables AI agents and LLMs to interact with Polaris Catalog Management, audit data governance and access control (RBAC) policies, and perform Iceberg table inspections using PyIceberg.

Example using PyIceberg to work with Iceberg in S3 via. Glue Data Catalog

A low-cost online Apache Iceberg lab using Cloudflare R2 Data Catalog

Apache Iceberg with PyIceberg (no Spark/JVM): catalog setup, time travel, CDC, schema evolution, upserts

Apache Polaris + PyIceberg で Iceberg REST Catalog を動かして確かめた実験記録（2026年7月時点）

provenance and immutability checks for iceberg lakehouses

Apache Iceberg feature store and data lakehouse on Backblaze B2 — versioned feature tables, schema evolution, snapshot rollback, and DuckDB time-travel queries via PyIceberg, with B2 as the warehouse (no data warehouse to run)

Postgres CDC → Kafka → Apache Iceberg with exactly-once, out-of-order merge (source-LSN high-water-mark) and a source-to-lakehouse reconciler that quantifies drift in dollars. Ships a Spark Structured Streaming job, a docker-compose CDC stack, and Terraform.

Locally reproducible Apache Iceberg lakehouse with read-only FastAPI/DuckDB serving, near-real-time micro-batch ingestion, and a read-only NL agent over the API. Containerized with CI/CD, single-host go-live (Caddy auto-HTTPS), and OpenTelemetry→Datadog observability. Live synthetic demo: https://demo.agentic-data-platform.me/docs

Provides a pyiceberg.io.FileIO implementation that uses hdfs-native client.

Data Lakehouse implementations showcasing two approaches: one built with Open Source technologies and another with Databricks