DBMS > Milvus

Milvus System Properties

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Editorial information provided by DB-Engines

Name

Description

A DBMS designed for efficient storage of vector data and vector similarity searches

Primary database model

Search engine

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.37
Rank	#259	Overall
	#17	Search engines

Website

milvus.io

Technical documentation

milvus.io/docs/overview.md

Initial release

2019

Current release

2.0, January 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++, Go

Server operating systems

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Typing

predefined data types such as float or date

Numeric and String

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

SQL

Support of SQL

APIs and other access methods

RESTful HTTP API

Supported programming languages

C++
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Foreign keys

Referential integrity

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

More information provided by the system vendor

Specific characteristics

Milvus is an open-source and cloud-native vector database built for production-ready AI. It was created to store,

index, and manage billion, or even trillion-scale embedding vectors generated by deep neural networks and other machine learning (ML) models.

As a database specifically designed to handle queries over vectors, it is capable of indexing vectors on a trillion 

scale. Unlike existing relational databases which mainly deal with structured data following a pre-defined 

pattern, Milvus is designed from the bottom-up to handle embedding vectors converted from unstructured data 

like emails, papers, IoT sensor data, Facebook photos, protein structures, and much more.

Competitive advantages

Highly available, versatile, and robust with millisecond latency.
Supports batch and stream data processing in real time.
Supports flexible scaling of each component by using Kubernetes to manage its execution engine and separating read, write and other services with microservices.
Supports Time Travel with distributed logging.
Supports heterogenous computing, which includes support for different types of hardware (CPU, GPU, FPGA, MLU) and instruction sets.
Supported by Rich APIs (Python, Node.js, Go, etc.) and tools (Milvus CLI, Attu, etc.) to facilitate DevOps.
Supports high performance ANN algorithms like FAISS，HNSW，ANNOY, etc.

Typical application scenarios

Video media: video understanding, video deduplication.
E-commerce and mobile applications: image understanding, reverse image search.
Finance/Telecommunications/Retail: AI-aided customer support, QA chatbots.
Internet: personalized recommender systems, personalized search.
Autonomous vehicles: automated data labeling and annotation, object detection.
Biopharmaceutical: virtual compound screening, compound retrosynthetic analysis, protein property prediction, and DNA testing.
Cybersecurity: malware detection and cyberattack alert.
Quantitative trading: data analysis and prediction.
Metaverse: environmental perception and interaction in virtual world.

See more in Milvus Bootcamp.

Key customers

Milvus is trusted by over 1,000 enterprises, including Baidu, eBay, IKEA, LINE, Shopee, Shutterstock, SmartNews,

Tencent, Tokopedia, TrendMicro, Walmart, and much more.

See Milvus Adopters for more Milvus users.

Market metrics

As of March 2022,

9.8k+ GitHub stars
1.4k+ Github forks
871k+ docker pulls
2k+ community members on Slack alone (represents only a portion of the community)

Licensing and pricing models

Milvus was released under the open-source Apache License 2.0 in October 2019.

Managed Cloud Service (coming soon).

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Top 10 Companies Working on Autonomous Mobile Robots in 2022
22 May 2022, Analytics Insight

Milvus, the AI Search Engine, Originally Developed by Zilliz Joins LF AI as New Incubation Project
10 April 2020, PR Newswire

What Is Vector Similarity Search? | Business Applications of Vector Search
11 August 2021, CIO Insight

Database technology evolves to combine machine learning and data storage
7 March 2022, VentureBeat

The Recommendation System
15 February 2022, News | Europeana Pro

provided by Google News

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