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DBMS > Milvus

Milvus Systemeigenschaften

Bitte wählen Sie ein weiteres System aus, um es mit Milvus zu vergleichen.

Unsere Besucher vergleichen Milvus oft mit Weaviate, Qdrant und PostgreSQL.

Redaktionelle Informationen bereitgestellt von DB-Engines
NameMilvus
KurzbeschreibungA DBMS designed for efficient storage of vector data and vector similarity searches
Primäres DatenbankmodellVektor DBMS
DB-Engines Ranking infomisst die Popularität von Datenbankmanagement- systemenranking trend
Trend Chart
Punkte1,47
Rang#171  Overall
#5  Vektor DBMS
Websitemilvus.io
Technische Dokumentationmilvus.io/­docs/­overview.md
Erscheinungsjahr2019
Aktuelle Version2.3.4, Jänner 2024
Lizenz infoCommercial or Open SourceOpen Source infoApache Version 2.0
Ausschließlich ein Cloud-Service infoNur als Cloud-Service verfügbarnein
DBaaS Angebote (gesponserte Links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Zilliz Cloud – Cloud-native service for Milvus
ImplementierungsspracheC++, Go
Server BetriebssystemeLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Typisierung infovordefinierte Datentypen, z.B. float oder dateVector, Numeric and String
XML Unterstützung infoVerarbeitung von Daten in XML Format, beispielsweise Speicherung von XML-Strukturen und/oder Unterstützung von XPath, XQuery, XSLTnein
Sekundärindizesnein
SQL infoSupport of SQLnein
APIs und andere ZugriffskonzepteRESTful HTTP API
Unterstützte ProgrammiersprachenC++
Go
Java
JavaScript (Node.js)
Python
Server-seitige Scripts infoStored Proceduresnein
Triggersnein
Partitionierungsmechanismen infoMethoden zum Speichern von unterschiedlichen Daten auf unterschiedlichen KnotenSharding
MapReduce infoBietet ein API für Map/Reduce Operationennein
Konsistenzkonzept infoMethoden zur Sicherstellung der Konsistenz in einem verteilten SystemBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Fremdschlüssel inforeferenzielle Integritätnein
Transaktionskonzept infoUnterstützung zur Sicherstellung der Datenintegrität bei nicht-atomaren Datenmanipulationennein
Concurrency infoUnterstützung von gleichzeitig ausgeführten Datenmanipulationenja
Durability infoDauerhafte Speicherung der Datenja
In-Memory Unterstützung infoGibt es Möglichkeiten einige oder alle Strukturen nur im Hauptspeicher zu haltenja
Berechtigungskonzept infoZugriffskontrolleRole based access control and fine grained access rights
Weitere Informationen bereitgestellt vom Systemhersteller
Milvus
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
  • RAG: retrieval augmented generation
  • 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 thousands of enterprises, including PayPal, eBay, IKEA, LINE, Shopee, Shutterstock, SmartNews, Tencent, Tokopedia, TrendMicro, Walmart, and much more.

See Milvus Adopters for more Milvus users.
Market metrics
As of January 2024,
  • 25k+ GitHub stars
  • 10M+ downloads and installations​
  • 3k+ enterprise adopters
Licensing and pricing models
Milvus was released under the open-source Apache License 2.0 in October 2019.

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Weitere Ressourcen
Milvus
DB-Engines Blog Posts

Vector databases
2. Juni 2023, Matthias Gelbmann

alle anzeigen

Erwähnungen in aktuellen Nachrichten

The Journey of RAG Development: From Notebook to Microservices
21. Februar 2024, Towards Data Science

What Is Milvus Vector Database?
6. Oktober 2023, The New Stack

AI-Powered Search Engine With Milvus Vector Database on Vultr
31. Januar 2024, SitePoint

Zilliz Cloud boosts vector database performance
31. Januar 2024, InfoWorld

Zilliz Cloud Adds Range Search
6. Februar 2024, iProgrammer

bereitgestellt von Google News



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