OpenMLDB
Milvus
Our great sponsors
OpenMLDB | Milvus | |
---|---|---|
9 | 104 | |
1,545 | 26,645 | |
2.0% | 3.6% | |
9.6 | 10.0 | |
2 days ago | 1 day ago | |
C++ | Go | |
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
Milvus
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Ask HN: Who is hiring? (April 2024)
Zilliz (zilliz.com) | Hybrid/ONSITE (SF, NYC) | Full-time
I am part of the hiring team for DevRel
NYC - https://boards.greenhouse.io/zilliz/jobs/4307910005
SF - https://boards.greenhouse.io/zilliz/jobs/4317590005
Zilliz is the company behind Milvus (https://github.com/milvus-io/milvus), the most starred vector database on GitHub. Milvus is a distributed vector database that shines in 1B+ vector use cases. Examples include autonomous driving, e-commerce, and drug discovery. (and, of course, RAG)
We are also hiring for other roles that I am not personally involved in the hiring process for such as product managers, software engineers, and recruiters.
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Unlock Advanced Search Capabilities with Milvus and Read about RAG
Get started with Milvus on GitHub.
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Milvus VS pgvecto.rs - a user suggested alternative
2 projects | 13 Mar 2024
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How to choose the right type of database
Milvus: An open-source vector database designed for AI and ML applications. It excels in handling large-scale vector similarity searches, making it suitable for recommendation systems, image and video retrieval, and natural language processing tasks.
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Simplifying the Milvus Selection Process
Selecting the right version of open-source Milvus is important to the success of any project leveraging vector search technology. With Milvus offering different versions of its vector database tailored to varying requirements, understanding the significance of selecting the correct version is key for achieving desired outcomes.
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7 Vector Databases Every Developer Should Know!
Milvus is an open-source vector database designed to handle large-scale similarity search and vector indexing. It supports multiple index types and offers highly efficient search capabilities, making it suitable for a wide range of AI and ML applications, including image and video recognition, natural language processing, and recommendation systems.
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Ask HN: Who is hiring? (February 2024)
Zilliz is hiring! We're looking for REMOTE and/or HYBRID roles in SF
Zilliz is the company behind Milvus (https://github.com/milvus-io/milvus), the most widely adopted vector database. Vector databases are a crucial piece of any technology stack looking to take advantage of unstructured data. Most recently and notably, Retrieval Augmented Generation (RAG). For RAG, vector databases like Milvus are used as the tool to inject customized data. In other words, vector databases make things like customized chat bots, personalized product recommendations, and more possible.
We are hiring for Developer Advocates, Senior+ Level Engineers and Product people, and Talent Acquisition. Check out all the roles here: https://zilliz.com/careers
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Qdrant, the Vector Search Database, raised $28M in a Series A round
Good on them, I know the crustaceans are out here happy about this raise for a Rust based Vector DB!
(now I'm gonna plug what I work on)
If you're interested in a more scalable vector database written in Go, check out Milvus (https://github.com/milvus-io/milvus)
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Open Source Advent Fun Wraps Up!
But before we do, I do want to say that 🤩 all these lovely Open-Source projects would love a little 🎉💕 love by getting a GitHub star ⭐ for their efforts. Including Open Source Milvus 🥰
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First 15 Open Source Advent projects
1. Milvus by Zilliz | Github
What are some alternatives?
Open3D - Open3D: A Modern Library for 3D Data Processing
pgvector - Open-source vector similarity search for Postgres
psychec - A compiler frontend for the C programming language
faiss - A library for efficient similarity search and clustering of dense vectors.
feathr - Feathr – A scalable, unified data and AI engineering platform for enterprise
qdrant - Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
libpmemobj-cpp - C++ bindings & containers for libpmemobj
Weaviate - Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
feast - Feature Store for Machine Learning
Elasticsearch - Free and Open, Distributed, RESTful Search Engine
featureform - The Virtual Feature Store. Turn your existing data infrastructure into a feature store.
Face Recognition - The world's simplest facial recognition api for Python and the command line