Getting started

You have many ways to get started with FeatureMesh:

  • Use the interactive snippets on this website to get acquainted with the FeatureQL language.
  • Install the pip library and use it from your code or notebooks on your own data.
  • Install the featuremesh-demos docker container for the full experience (analytics proxy, real-time serving...).

Using FeatureMesh on this website

Nothing to install here, just use the 200+ interactive snippets on this website.

Starting with this one:

Javascript will transmit your FeatureQL queries to the remote FeatureMesh server, then execute the SQL query it got back in duckdb, using the duckdb wasm module in your browser.

Using FeatureMesh with the pip library

pip install featuremesh
bash

The featuremesh library provides a client that can be used to interact with the FeatureMesh registry and online service.

You will need to provide a query executor to run the queries locally.

Using the featuremesh-demos docker

The featuremesh-demos docker container includes a full FeatureMesh setup with proxy and online service.

It also includes:

  • Jupyter notebooks
  • Several possible online backends such as redis, postgres, http server, etc.
  • Many notebooks to understand different aspects of FeatureMesh, including:
    • Analytics with BigQuery
    • Federated online serving

It is the perfect environment to get started with all the possibilities of FeatureMesh, for batch analytics or real-time serving.

More details here: https://github.com/featuremesh/featuremesh-demos

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Last update at: 2025/11/06 07:00:15
Last updated: 2025-11-06 07:00:51