archestra
★ 4.4k
vs
lakevision
★ 52
archestra vs lakevision
archestra: Archestra is a secure, MCP-native AI platform that simplifies enterprise AI adoption. It provides comprehensive tools for AI orchestration, security against prompt injections and data exfiltration, cost management, and observability across the organization.; lakevision: 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.
01
TL;DR
archestraObservability · ★ 4.4k
When to choose:
- You are a platform or security team that needs central control over how the company uses models and MCP servers.
- You want one platform covering an internal chat, an LLM gateway, an MCP gateway and registry, and an agent runtime.
- You need SSO, RBAC, sandboxed code execution, guardrails, per-user tool authorisation, OpenTelemetry and Prometheus.
When to skip:
- You are a small team that only needs a proxy: Kubernetes-oriented components make this a significant deployment.
- You need to avoid AGPL or commercial terms: the default code is AGPL-3.0 and parts marked Enterprise are under a commercial licence.
- You already run gateways or chat apps whose roles overlap; plan what it would replace.
lakevisionObservability · ★ 52
Quickly understand the data layout, file locations, and change history within an Apache Iceberg-based Data Lakehouse.
02
Side-by-Side Comparison
Field
archestralakevisionCategory
Observability
Observability
Stars
★ 4.4k
★ 52
License
AGPL-3.0 (enterprise parts under a commercial license)
Apache-2.0
Install Command
docker pull archestra/platform:latest; docker run -p 9000:9000 -p 3000:3000 -e ARCHESTRA_QUICKSTART=true -v /var/run/docker.sock:/var/run/docker.sock -v archestra-postgres-data:/var/lib/postgresql/data -v archestra-app-data:/app/data archestra/platform;
git clone https://github.com/lakevision-project/lakevision.git && cd lakevision && docker build -t lakevision:1.0 . && docker run --env-file .env -p 8081:8081 lakevision:1.0 /app/start.sh
Updated
1d ago
1mo ago
Open Source
Yes
Yes
Tags
AI Platform, AI Security, Kubernetes
Data Lakehouse, Apache Iceberg, Data Catalog
03
Features
archestra01Secure, MCP-native AI Platform for simplified enterprise AI usage.
02Private MCP registry with governance and ChatGPT-like chat capabilities.
03Kubernetes-native orchestration for managing AI servers and credentials.
04Advanced security features to prevent prompt injections and data exfiltration.
05Comprehensive cost monitoring, dynamic optimization, and observability tools.
lakevision01Search 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.
04
Use Cases
archestra↳Centralized orchestration and secure management of AI models and data for platform teams.
↳Secure deployment and development of AI agents across the organization for developers.
↳Facilitating organization-wide AI adoption, cost reduction, and usage visibility for management.
lakevision↳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
Best For
archestraEssentialTrending
lakevision—
FAQ
FAQ
What is the difference between archestra and lakevision?
Both archestra and lakevision are in the Observability category. archestra has 4.4k stars, while lakevision has 52 stars.
Which is better, archestra or lakevision?
The best choice depends on your use case. Choose archestra if Centralized orchestration and secure management of AI models and data for platform teams., and lakevision if Quickly understand the data layout, file locations, and change history within an Apache Iceberg-based Data Lakehouse..
Is archestra free or open source?
Yes, archestra is open source on GitHub (AGPL-3.0 (enterprise parts under a commercial license)).
Is lakevision free or open source?
Yes, lakevision is open source on GitHub (Apache-2.0).
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