dbt Semantic Layer vs Ibis
dbt Semantic Layer
getdbt.comIbis
ibis-project.orgSide by side
| Figure | dbt Semantic Layer | Ibis |
|---|---|---|
| Price from | $0.09/mo | Free |
| Free plan | Yes | Yes |
| Free trial | Yes | — |
| Open source | — | — |
| Web | Yes | — |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| API | Yes | Yes |
| Self-hosted | — | Yes |
| Plans published | 5 | 1 |
| Spec score · Data Transformation Tools | 8.9 (#8) | 8.5 (#12) |
| Integrations | The product page says the Semantic Layer offers an API, the dbt MCP Server, and dozens of out-of-the-box integrations for BI, notebooks, spreadsheets, embedded analytics, and AI systems. | The documented Python data integrations include pandas and Polars, with visualization tools such as matplotlib, seaborn, Plotly, Vega-Altair and plotnine. |
| Security and compliance | The dbt Labs Trust Center lists SOC 2 Type II, ISO 27001:2022, ISO 27017, ISO 27018, ISO 42001, GDPR, and CCPA badges. | The opened official pages do not state security certifications or compliance claims. |
| Support | The pricing page lists 24x5 support for Starter and priority support with SLAs for Enterprise. | For help, the project points users to GitHub and Zulip, and says Voltron Data offers commercial support for Ibis. |
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.
Ibis
Ibis is a free, open-source Python dataframe library that provides a consistent API across more than 20 query backends. It lets users compose SQL and Python dataframe code, bringing data engineering and data science workflows together. For local dataframes, Ibis uses DuckDB by default and also names Polars and DataFusion. The project describes a workflow that can start locally and move to remote execution by changing a single line of code.
Ibis supports and tests Google BigQuery, Snowflake, Databricks Cloud, and Amazon Athena; support for those cloud backends could move to best effort if funding ends. Supported data formats include CSV, TSV, JSON, Parquet, Delta Lake, and Avro. Install Ibis with a supported backend using pip, conda, mamba, or pixi. One package distinction matters: the PyPI package named ibis is separate from ibis-framework, and the two cannot coexist in one Python environment because both use the ibis module name. Operation coverage varies by backend due to differences in SQL dialects and upstream support. The project recommends GitHub and Zulip for help, and Voltron Data offers commercial support.