Ibis vs Miller
Ibis
ibis-project.orgMiller
miller.readthedocs.ioSide by side
| Figure | Ibis | Miller |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| API | Yes | — |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · Data Transformation Tools | 8.5 (#12) | 7.6 (#25) |
| Integrations | The documented Python data integrations include pandas and Polars, with visualization tools such as matplotlib, seaborn, Plotly, Vega-Altair and plotnine. | The documentation describes Miller as complementary to R, pandas, SQL databases, and the Unix toolkit. |
| Support | For help, the project points users to GitHub and Zulip, and says Voltron Data offers commercial support for Ibis. | The project directs users to GitHub Discussions for general questions, Stack Overflow for tagged questions, and GitHub Issues for bug reports and feature requests. |
Plans
In their own words
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.
Miller
Miller has no write-up on Specifiction yet; its figures are above.