Ibis vs Polars
Ibis
ibis-project.org
Polars
pola.rsSide by side
| Figure | Ibis | Polars |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | Yes |
| Open source | — | — |
| Web | — | Yes |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · Data Transformation Tools | 8.5 (#12) | 7.7 (#20) |
| Integrations | The documented Python data integrations include pandas and Polars, with visualization tools such as matplotlib, seaborn, Plotly, Vega-Altair and plotnine. | The homepage lists support for CSV, JSON, Parquet, Delta Lake, AVRO, Excel, Feather, Arrow, several databases, and cloud storage. |
| Product | Ibis is a portable Python dataframe library that provides one API for more than 20 data backends. | Polars is an open-source DataFrame library for data manipulation, described as a fast single-machine data processing solution with a typed, expressive API. |
| Security | The reviewed official pages do not state security certifications or compliance claims. | Polars says Polars Cloud compute runs in the customer's cloud environment and that customer data does not leave that environment. |
| Support | For help, the project points users to GitHub and Zulip, and says Voltron Data offers commercial support for Ibis. | Polars Cloud offers team support for technical questions, implementation guidance, and product feedback. |
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.
Polars
Polars is an open-source DataFrame library for data manipulation, designed for single-machine processing with a typed, expressive API. Its multithreaded query engine is written in Rust and uses vectorized columnar processing to execute work in parallel. A query optimizer selects an execution plan, and the streaming API can process datasets larger than memory without holding all results in memory. Installation examples cover Python, Rust, and JavaScript. Supported formats include CSV, JSON, Parquet, Delta Lake, Avro, Excel, Feather, and Arrow IPC; the homepage also lists databases and cloud storage. Polars can read and write data in AWS S3, Azure Blob Storage, and Google Cloud Storage. The open-source library costs nothing under the MIT license. Polars Cloud runs distributed queries through the Polars API and scales work from local execution to a cluster; it is available on AWS. Its 30-day trial begins when an organization connects its first workspace to AWS, and its compute runs in the customer's cloud environment. Polars On-Prem supports Kubernetes and bare-metal deployments, including air-gapped Enterprise deployments.