featureform
hopsworks
Our great sponsors
featureform | hopsworks | |
---|---|---|
28 | 4 | |
1,674 | 1,071 | |
1.1% | 1.1% | |
9.7 | 9.3 | |
6 days ago | 8 days ago | |
Jupyter Notebook | Java | |
Mozilla Public License 2.0 | GNU Affero General Public License v3.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
featureform
- Still look familiar?
- Featureform: A Python Framework for the Entire Feature Lifecycle. Define, Version, Orchestrate, & Deploy ML Features with OSS Featureform!
- Does this look familiar?
- Does this look familiar? Define, Manage, & Serve your ML Features with OSS Featureform!
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What’s your process for deploying a data pipeline from a notebook, running it, and managing it in production?
Feature store: new hot one: https://www.featureform.com/
- featureform / featureform :
- Featureform: An Open-Source Feature Store for your ML Features
hopsworks
- Hopworks: MLOps platform with Python-centric Feature Store
- Show HN: Feature Store and Model Registry; Hopsworks 3.0
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[D] Your 🫵 Preferred Feature Stores?
Anyways -> https://github.com/logicalclocks/hopsworks
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Reflections on the Lack of Adoption of Domain Specific Languages [pdf]
We built the first open-source feature store for ML, https://github.com/logicalclocks/hopsworks , when every existing proprietary feature store (Uber Michelangelo and Bighead at AirBnb) were shouting about how their DSL for feature engineering was the future.
Fast-forward 2 years and it is clear that Data Scientists want to work with Python, not with a DSL. We based our Feature Store on a Dataframe API for Python/PySpark. The DSL can never evolve at the same rate as libraries in a general-purpose programming language. So, your DSL is great for show-casing a Feature Store, but when you need to compute embeddings or train a GAN or done any type of feature engineering that is not a simple time-window aggregation, you pull out Python (or Scala/Java). I am old enough to have seen many DSLs in different domains (GUIs, aspect-oriented programming, feature engineering) have their day in the sun only to be replaced by general-purpose programming languages due to their unmatched utility.
What are some alternatives?
feast - Feature Store for Machine Learning
feathr - Feathr – A scalable, unified data and AI engineering platform for enterprise
Milvus - A cloud-native vector database, storage for next generation AI applications
textX - Domain-Specific Languages and parsers in Python made easy http://textx.github.io/textX/
awesome-vector-search - Collections of vector search related libraries, service and research papers
OpenMLDB - OpenMLDB is an open-source machine learning database that provides a feature platform computing consistent features for training and inference.
iwlearn - "Production First" Machine Learning Framework
vald - Vald. A Highly Scalable Distributed Vector Search Engine
serverless-ml-course - Serverless Machine Learning Course for building AI-enabled Prediction Services from models and features