Jenner is SAS-compatible and runs the SAS language natively on macOS, including Apple silicon. No SAS license is required. Open a program you already have, run it, and get your output — on the laptop in front of you.
Jenner is built for macOS as a first-class target and runs natively on Apple silicon. It installs as a single self-contained binary: no SAS license, no virtual machine to configure, no second operating system to maintain, and no remote session to connect to. Your programs run at full native speed, and your data stays on your own machine.
Programs stay in SAS syntax, so the files on your disk are the files you run. Work from the command line, from a Jupyter notebook using the native kernel, or from the editor you already use. Because it is one binary, getting started is a download rather than a project.
Jenner is SAS-compatible: the language your programs are already written in, running on macOS with the same statement and option names you use today, and no SAS license required.
The core of the language runs as written — DATA step logic, arrays, formats and informats, the macro facility, and PROC SQL. Programs keep their existing structure, so there is no porting step to complete before you can run something and see output.
Regression and linear modeling, survival analysis, multivariate methods and clustering, time series, quality control, survey analysis, design of experiments, matrix programming, and ODS Graphics. Each procedure has its own reference page listing the statements and options it supports.
Jenner reads and writes SAS7BDAT and XPT directly on macOS, alongside CSV and Parquet. Nothing needs converting before you start, and output can go back out in the same formats — so a program on your Mac can hand its results to a colleague working on Windows.
The same source runs on macOS, Windows, and Linux. A program developed on a Mac runs unchanged on a Linux server, which makes a laptop a reasonable place to build work that is destined for a scheduler.
Jenner passes all 58 datasets in the NIST Statistical Reference Datasets benchmark — the standard third-party accuracy suite for statistical software — and cross-validates its statistical procedures against the Python (statsmodels) and R implementations. To confirm it against your own work, run a program and compare the output datasets with PROC COMPARE.
Native on Apple silicon. No virtual machine, no SAS license.
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