OpenMLDB
feathr
Our great sponsors
OpenMLDB | feathr | |
---|---|---|
9 | 9 | |
1,550 | 1,929 | |
2.3% | 1.2% | |
9.6 | 6.7 | |
1 day ago | 21 days ago | |
C++ | Scala | |
Apache License 2.0 | Apache License 2.0 |
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.
OpenMLDB
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Comparative Analysis of Memory Consumption: OpenMLDB vs Redis Test Report
b. Pull the testing code
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Ultra High-Performance Database OpenM(ysq)LDB: Seamless Compatibility with MySQL Protocol and Multi-Language MySQL Client
OpenMLDB has introduced a new service module called OpenM(ysq)LDB, expanding its capabilities to integrate with MySQL infrastructure. This extension redefines the “ML” in OpenMLDB to signify both Machine Learning and MySQL compatibility. Through OpenM(ysq)LDB, users gain the ability to utilize MySQL command-line clients or MySQL SDKs in various programming languages, enabling seamless access to OpenMLDB’s unique online and offline feature calculation capabilities.
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Mastering Distributed Database Development in 10 Minutes with OpenMLDB Developer Docker Image
OpenMLDB is an open-source, distributed in-memory database system designed for time-series data. It focuses on high performance, reliability, and scalability, making it suitable for handling massive time-series data and real-time computation of online features. In the wave of big data and machine learning, OpenMLDB has emerged as a promising player in the open-source database field, thanks to its powerful data processing capabilities and efficient support for machine learning.
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OpenMLDB new release v0.8.4
For detailed release notes, please refer to: https://github.com/4paradigm/OpenMLDB/releases/tag/v0.8.4 Feel free to try it out, and discuss it in the official Slack channel (https://join.slack.com/t/openmldb/shared_invite/zt-ozu3llie-K~hn9Ss1GZcFW2~K_L5sMg) if you have any thoughts on improvements or questions!
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Quickstart with OpenMLDB
New to OpenMLDB? Check out the quick workflow and quickstart blog post!
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Engineering Practice for Real-time Feature Store in Decision-Making Machine Learning
Website: https://openmldb.ai/
- [D] Your 🫵 Preferred Feature Stores?
- OpenMLDB: An new open-source database for production AI/ML workloads
feathr
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[D] good feature store?
For open source/free feature stores, look into Feathr https://github.com/feathr-ai/feathr and Feast https://feast.dev/.
- Open sourcing Feathr – LinkedIn’s feature store for productive machine learning
- Show HN: Feathr – An Open-Source, Enterprise-Grade Virtual Feature Store
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[P] Feathr - An Open-Source, Enterprise-Grade and High-Performance Feature Store
Open Sourcing Feathr
- [D] Your 🫵 Preferred Feature Stores?
- Feathr – LinkedIn Open Sourced Its Feature Store
- Feathr – an enterprise-grade, high performance feature store
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LinkedIn Open-Sources ‘Feathr’, It’s Feature Store To Simplify Machine Learning (ML) Feature Management And Improve Developer Productivity
LinkedIn research team has recently open-sourced feature store, Feathr, created to simplify machine learning (ML) feature management and increase developer productivity. Feathr is used by dozens of LinkedIn applications to define features, compute them for training, deploy them in production, and share them across consumers. Compared to previous application-specific feature pipeline solutions, Feathr users reported significantly reduced time required to add new features to model training and improved runtime performance.
What are some alternatives?
Open3D - Open3D: A Modern Library for 3D Data Processing
hopsworks - Hopsworks - Data-Intensive AI platform with a Feature Store
psychec - A compiler frontend for the C programming language
feast - Feature Store for Machine Learning
libpmemobj-cpp - C++ bindings & containers for libpmemobj
featureform - The Virtual Feature Store. Turn your existing data infrastructure into a feature store.
metarank - A low code Machine Learning personalized ranking service for articles, listings, search results, recommendations that boosts user engagement. A friendly Learn-to-Rank engine
Clustering4Ever - C4E, a JVM friendly library written in Scala for both local and distributed (Spark) Clustering.
MNN - MNN is a blazing fast, lightweight deep learning framework, battle-tested by business-critical use cases in Alibaba
CIlib - Typesafe, purely functional Computational Intelligence