I’ve been really impressed with Ibis so far. Modern data stacks need to be flexible passing data between PostgreSQL, dataframes, and analytics dbs like DuckDB or ClickHouse. Super helpful to have one common query language connecting these data sources

The other popular choices are Confidence and Ambrosia. They slightly differ in features: tea-tasting covers some methods not covered in these packages, and vice versa. Ultimately, tea-tasting aims to cover all the essential methods. But the biggest difference is the support for

Here are a few reasons why I prefer using Ibis over Pandas/polars data ( bdw I still use Polars or Data Fusion as the engine ) - Ibis is lightweight and directly executes queries on the underlying databases, functioning more as a result transporter than a heavy framework. -

My SciPyConf talk: Ibis and DuckDB geospatial: a match made on Earth! is on youtube. (there was a problem with the recording, apologies about the yellow background) #geospatial youtu.be/xQnHhPMgWdM

end of an era, for new project think seriously of using a new Dataframe Engine, there are plenty of choices, ibis will drop support for Pandas ibis-project.org/posts/farewell…

Ibis support is very rudimentary but you can connect to #microsoftfabric DWH, list catalog, run sql etc

This is super exciting. Ibis coming to marimo github.com/marimo-team/ma…

The "Tools don't matter" argument falls flat in Data Engineering and ML. - Working with large datasets on a Spark cluster can quickly shift your focus from business problems to infrastructure challenges. - Using Pandas for 10GB+ data demands huge RAM, but switching to DuckDB

Want to work with Python dataframes on a trillion rows of data in someone else's high-performane OLAP database? Check out our latest blog using Ibis, ClickHouse , and Shiny for Python to build an interactive dashboard on the PyPI downloads dataset: ibis-project.org/posts/better-p…

It's never been a better time to get involved with Ibis! If you need Python dataframes that work on the best local engines (DuckDB, ApacheDataFusion, polars data) and distributed/cloud platforms (Apache Spark, SnowflakeDB, ClickHouse, Trino), give us a try!

no code transformations using marimo's mo.ui.dataframe and Ibis! Pass in any Ibis dataframe to mo.ui.dataframe to display a UI for different filters/transformations and get the filtered result back in Python. Plus, you can see the SQL statement generated by Ibis!

First blog post in a long time! I started writing a post ~2 years ago on adventures counting 130M U.S. buildings by zipcode and finally circled back to write it up. Everybody is a winner really, but DuckDB Ibis , ApacheArrow, and GeoParquet were essential throughout!

Hi y'all, I'll be talking at #DuckCon on January 2025. I'll be sharing how to leverage the power of DuckDB's geospatial capabilities while staying within the Python ecosystem using Ibis . I’ll show you how to work with GeoParquet data and create nice maps in your laptop.

With the latest version of Pyodide (0.27.1), you can run %pip install ibis-framework[duckdb] to get an expressive, lightning-fast, and *entirely-in-browser* dataframe API! Give it a try at ibis-project.org/tutorials/brow…

Ibis 10.0.0 is out! pip install ibis-framework==10.0.0 Lots of new features, bug fixes and two new backends: Amazon Athena and Databricks! Check out the release notes here: ibis-project.org/release_notes#…

New blog posts 1/2: Does Ibis Understand SQL? ibis-project.org/posts/does-ibi…

New blog posts 2/2: Dynamic UDF Rewriting with Predicate Pushdowns ibis-project.org/posts/udf-rewr… Check 'em out!