OpenMLDB
featureform
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OpenMLDB | featureform | |
---|---|---|
9 | 28 | |
1,545 | 1,674 | |
2.0% | 1.1% | |
9.6 | 9.7 | |
2 days ago | 1 day ago | |
C++ | Jupyter Notebook | |
Apache License 2.0 | Mozilla Public 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
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
What are some alternatives?
Open3D - Open3D: A Modern Library for 3D Data Processing
feast - Feature Store for Machine Learning
psychec - A compiler frontend for the C programming language
Milvus - A cloud-native vector database, storage for next generation AI applications
feathr - Feathr – A scalable, unified data and AI engineering platform for enterprise
libpmemobj-cpp - C++ bindings & containers for libpmemobj
awesome-vector-search - Collections of vector search related libraries, service and research papers
hopsworks - Hopsworks - Data-Intensive AI platform with a Feature Store
MNN - MNN is a blazing fast, lightweight deep learning framework, battle-tested by business-critical use cases in Alibaba
vald - Vald. A Highly Scalable Distributed Vector Search Engine