dbt Semantic Layer vs Zenlytic Metrics Layer
dbt Semantic Layer
getdbt.comZenlytic Metrics Layer
github.comSide by side
| Figure | dbt Semantic Layer | Zenlytic Metrics Layer |
|---|---|---|
| Price from | $0.09/mo | Free |
| Free plan | Yes | Yes |
| Free trial | Yes | — |
| Open source | — | — |
| Web | Yes | — |
| API | Yes | Yes |
| Plans published | 5 | 1 |
| Spec score · Semantic Layer Software | 9.2 (#2) | 7.0 (#23) |
| Headquarters | Oakland, California, United States | New York, NY |
| Purpose | The Semantic Layer centralizes metric definitions on dbt models and automatically handles data joins for consistent use across downstream tools and applications. | Metrics Layer is an open-source project intended to make access to metrics consistent across an organization. |
| Support | The pricing page lists 24x5 support for Starter and priority support with SLAs for Enterprise. | Zenlytic's support policy lists email support for technical issues, account configuration, data connectivity, and billing questions, plus an AI support agent available 24/7. |
| Warehouse support | The Semantic Layer documentation identifies Snowflake, BigQuery, Databricks, and Redshift as supported data platforms. | The repository lists Snowflake, BigQuery, Postgres, Druid, DuckDB, SQL Server, and Redshift, with Druid, DuckDB, and SQL Server limited to SQL compilation rather than query execution. |
Plans
dbt Semantic Layer
- DeveloperFree
- dbt State add-on$0.09 a month
- Starter$100 a month
- EnterprisePriced on request
- Enterprise+Priced on request
In their own words
dbt Semantic Layer
The dbt Semantic Layer centralizes metric definitions on dbt models and handles joins so downstream tools and applications can use metrics consistently. MetricFlow generates SQL at query time from semantic model and metric configurations. Teams define those models and metrics in YAML as version-controlled, lineage-aware code. MetricFlow can optimize joins, rewrite queries to reduce compute and latency, and cache repeated queries. The product offers an API, the dbt MCP Server and integrations for BI tools, notebooks, spreadsheets, embedded analytics and AI systems. GraphQL and JDBC APIs and a Python SDK provide ways to query metrics and dimensions; Claude and ChatGPT can connect to governed metrics through the MCP server. Documented warehouse platforms include Snowflake, BigQuery, Databricks and Redshift. Defining and querying metrics requires a dbt Starter or Enterprise-tier account, and single-tenant accounts need account-representative setup and enablement. Starter includes 5,000 queried metrics per month; Enterprise and Enterprise+ each include 20,000. Starter costs $100 a month per user. The free Developer plan does not list the Semantic Layer.
Zenlytic Metrics Layer
Zenlytic Metrics Layer has no write-up on Specifiction yet; its figures are above.