Technology · Product

Milvus

Product · Catalog tech@1

Vector database for similarity search.

Matched as
  • milvus

Momentum

Each signal is ranked as a percentile among the technologies that have it. A signal without enough history is not counted, and never shown as zero. How momentum works

Momentum

Collecting0 of 5 signals

No score yet. Momentum is published only when at least 2 of the 5 signals have history. Milvus has 0, so there is no single number: each signal is shown on its own below. It is not a zero, and nothing is estimated in its place.

Snapshot OCT 24, 2026 · Scoring tech@1

Official repository stars
Collecting
Star growth needs repository snapshots 30 days apart.46,301 stars now
Member repository stars
Collecting
Star growth needs repository snapshots 30 days apart.0 new members in 30 days
Package adoption
Not published by its registries
Its packages’ registries publish no adoption figure, so there is nothing to grow.
Open models
No official models
No official model on Hugging Face, so this signal does not apply.
News
Collecting
News counts once there are 3 events across the last 60 days; it has 0.0 in the last 30 days · 0 in the 30 before

Adoption by registry

The growth of Milvus’s own packages, one row per registry in that registry’s own unit. Registries count different things over different windows, so they are never added together.

No registry has two observations of Milvus’s own packages about 30 days apart yet, so there is no growth to show. Nothing is estimated in its place.

News activity

Events · 7 days
0published events that mention it
Events · 30 days
0published events that mention it
Previous 30 days
0events in the 30 days before

Momentum history

Momentum history starts OCT 8, 2026. A chart appears once two daily snapshots carry a score; none does so far.

Repositories

Official 1

  • milvus-io/milvus

    Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search

    Official repositoryGo

    46.3K stars

Members 13repositories tagged with one of its aliases, most-starred first

Packages

“Is” packages are Milvus itself; ecosystem packages depend on them. The two are counted separately and never added together. Adoption is each registry’s own figure, with its percentile within that registry.

Is 1the technology itself, most-adopted first

  • pymilvus

    Python SDK for Milvus

    Listed in the catalogPyPI

    Not published by PyPI

Ecosystem 12packages that depend on it, most-adopted first

  • autorag

    Automatically Evaluate RAG pipelines with your own data. Find optimal structure for new RAG product.

    Depends on pymilvusPyPI

    Not published by PyPI
  • deepsearcher

    None

    Depends on pymilvusPyPI

    Not published by PyPI
  • dynamiq

    Dynamiq is an orchestration framework for agentic AI and LLM applications

    Depends on pymilvusPyPI

    Not published by PyPI
  • langbot

    Production-grade platform for building agentic IM bots

    Depends on pymilvusPyPI

    Not published by PyPI
  • langchain-milvus

    An integration package connecting Milvus and LangChain

    Depends on pymilvusPyPI

    Not published by PyPI
  • llama-index-vector-stores-milvus

    llama-index vector_stores milvus integration

    Depends on pymilvusPyPI

    Not published by PyPI
  • nvidia-nat-core

    Core library for NVIDIA NeMo Agent Toolkit

    Depends on pymilvusPyPI

    Not published by PyPI
  • omagent-core

    Core package for OmAgent

    Depends on pymilvusPyPI

    Not published by PyPI
  • paddle-pipelines

    Paddle-Pipelines: An End to End Natural Language Proceessing Development Kit Based on PaddleNLP

    Depends on pymilvusPyPI

    Not published by PyPI
  • rasa-pro

    State-of-the-art open-core Conversational AI framework for Enterprises that natively leverages generative AI for effortless assistant development.

    Depends on pymilvusPyPI

    Not published by PyPI
  • trustrag

    RAG Framework within Reliable input,Trusted output

    Depends on pymilvusPyPI

    Not published by PyPI
  • vectordb-bench

    VectorDBBench is not just an offering of benchmark results for mainstream vector databases and cloud services, it's your go-to tool for the ultimate performance and cost-effectiveness comparison. Designed with ease-of-use in mind, VectorDBBench is devised to help users, even non-professionals, reproduce results or test new systems, making the hunt for the optimal choice amongst a plethora of cloud services and open-source vector databases a breeze.

    Depends on pymilvusPyPI

    Not published by PyPI

Latest news the 0 latest events that mention it

No published news event mentions Milvus yet.