lakevision
Active·★ 52·Apache-2.0·Updated 2026-09-01
Lakevision is a comprehensive tool designed to provide deep insights into Data Lakehouses built on the Apache Iceberg table format. It allows users to explore namespaces, tables, schemas, properties, and change history, facilitating efficient data governance and understanding.
#Data Lakehouse#Apache Iceberg#Data Catalog#Data Governance#Data Quality#Observability#FastAPI#SvelteKit
01
Features
01Search and view all namespaces and tables, including their schema, properties, partition specs, and snapshots.
02Graphical summary of record additions over time and detailed partition information like record count, file count, and size.
03Lakehouse Health Feature for running, scheduling, and monitoring data quality and health checks.
04OIDC/OAuth-based authentication support and pluggable authorization for secure access control.
05Optional "Chat with Lakehouse" capability using an LLM.
02
Compatibility
Python
Runtime
Verified via docs
Node.js
Frontend Runtime
Verified via docs
Docker
Containerization
Verified via docs
Linux
OS
Verified via docs
macOS
OS
Verified via docs
Apache Iceberg
Data Format
Verified via docs
03
Quick start
1
$ git clone https://github.com/lakevision-project/lakevision.git
2
$ cd lakevision
3
$ docker build -t lakevision:1.0 .
4
$ docker run --env-file .env -p 8081:8081 lakevision:1.0 /app/start.sh
04
Use cases
↳Quickly understand the data layout, file locations, and change history within an Apache Iceberg-based Data Lakehouse.
↳Implement and monitor data quality standards and health checks across your lakehouse environment.
↳Securely manage and govern data access by integrating OIDC/OAuth authentication and custom authorization plugins.
↳Explore and analyze table-level metadata, such as schemas, partition details, and snapshots, for data management tasks.
↳Deploy a robust data lakehouse observability solution on Kubernetes or OpenShift for production environments.
05
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