Polars

Query profiles in Polars Nanook can now be shared.

Send a profile to a colleague when you want a second opinion on your query's performance. They see the plan, the stages and the metrics, without needing an account themselves.

Blog post: pola.rs/posts/share-qu…

Query Profile: nanook.pola.rs/portal/share/q…

Introducing Polars Nanook.

Polars Nanook is our next generation data platform for high performance scalable workloads on cloud and on-premise for either humans or agents.

Aside from the rebrand, we've been able to ship very big features:

- SQL support
- Huge leap in coverage distributed algorithms
- GPU support
- Faster than any Spark accelerator we can find

pola.rs/posts/polars-c…

Polars 2.1 is released!

Three weeks after 2.0 we're shipping a big one. A few highlights:

- Spill to disk for group-by and window functions
- Recursive CTE's in SQL
- Reading and writing encrypted Parquet
- Better memory tracking for out-of-core
- And over 90 performance improvements merged

Link below

We ran Polars 2.0 SQL, DuckDB and DataFusion on an @nvidia Vera CPU and compared it to an Intel Xeon 6, m8id.metal-96xl.

On the NVIDIA Vera, Polars ran 2 to 2.5x faster compared to Xeon, and 2 to 3x faster than the runner-up.

pola.rs/posts/nvidia_v…

We just released Polars 2.0.

It removed many of our legacy decisions makes the streaming engine our default and promotes SQL to a first class citizen within Polars.

It comes with initial out-of-core (spill to disk) support, a new Map data type and a lot of performance improvements. In fact, we think Polars is now one of the fastest analytical SQL engines on a single node. See benchmarks in the post: pola.rs/posts/release-…