Zenlytic Metrics Layer review
A self-hosted semantic layer for governed metrics, access controls, and warehouse querying.
Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
Zenlytic Metrics Layer is an open-source Python project for analytics teams that need consistent metric and dimension definitions across an organization. It reads YAML data models, connects to supported data warehouses, and exposes modeled data through a Python client or SQL using MQL. The model includes reusable views, measures, explicit relationships, field mappings, access grants, and row-level access filters. Its self-hosted deployment model suits teams that want control over the metrics layer and its access rules.
The strongest fit is governed metric access across varied warehouse structures. Zenlytic supports Snowflake, BigQuery, Postgres, Druid, DuckDB, SQL Server, and Redshift, while field mappings can connect tables that cannot be joined directly. Row-level filters, along with column, view, and topic grants, provide several ways to control what different users or groups can access. Centralized definitions also give teams a shared modeling layer rather than relying on separate metric logic in individual queries.
Query access is available through both Python and SQL with MQL, and the layer can compile or run queries depending on the warehouse. That makes it relevant for teams working across analytical workflows, although the supported BI fit is centered on Zenlytic. Teams should also expect to manage a self-hosted, open-source project rather than adopt a managed service. Zenlytic Metrics Layer is a strong choice for open-source teams prioritizing governed metrics and granular access controls; teams seeking built-in AI features, a managed deployment, or broader documented BI compatibility should consider another option.
Zenlytic Metrics Layer pros and cons
- Where it wins
- Centralizes metrics, dimensions, measures, relationships, and joins
- Supports row-level, column, view, and topic access grants
- Queries modeled data through Python or SQL with MQL
- Where it doesn't
- Requires self-hosted deployment and operational ownership
- Works with Zenlytic as its supported BI tool
- Does not provide documented AI features
Zenlytic Metrics Layer fact sheet, pricing and score →
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