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DBMS > Milvus vs. YottaDB

System Properties Comparison Milvus vs. YottaDB

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Editorial information provided by DB-Engines
NameMilvus  Xexclude from comparisonYottaDB  Xexclude from comparison
DescriptionA DBMS designed for efficient storage of vector data and vector similarity searchesA fast and solid embedded Key-value store
Primary database modelVector DBMSKey-value store
Secondary database modelsRelational DBMS infousing the Octo plugin
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.02
Rank#90  Overall
#5  Vector DBMS
Score0.18
Rank#316  Overall
#47  Key-value stores
Websitemilvus.ioyottadb.com
Technical documentationmilvus.io/­docs/­overview.mdyottadb.com/­resources/­documentation
DeveloperYottaDB, LLC
Initial release20192001
Current release2.4.4, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoAGPL 3.0
Cloud-based only infoOnly available as a cloud servicenono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Zilliz Cloud – Cloud-native service for Milvus
Implementation languageC++, GoC
Server operating systemsLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Docker
Linux
Data schemeschema-free
Typing infopredefined data types such as float or dateVector, Numeric and Stringno
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nono
Secondary indexesnono
SQL infoSupport of SQLnoby using the Octo plugin
APIs and other access methodsRESTful HTTP APIPostgreSQL wire protocol infousing the Octo plugin
Proprietary protocol
Supported programming languagesC++
Go
Java
JavaScript (Node.js)
Python
C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust
Server-side scripts infoStored proceduresno
Triggersno
Partitioning methods infoMethods for storing different data on different nodesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlRole based access control and fine grained access rightsUsers and groups based on OS-security mechanisms
More information provided by the system vendor
MilvusYottaDB
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
» more
Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
» more
Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
Key customersMilvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
Market metricsAs of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
» more
Licensing and pricing modelsMilvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

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More resources
MilvusYottaDB
DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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Recent citations in the news

How NVIDIA GPU Acceleration Supercharged Milvus Vector Database
26 March 2024, The New Stack

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

10 top vector database options for similarity searches
8 August 2024, TechTarget

Milvus in 2023: Open Source Vector Database Year in Review
19 January 2024, The New Stack

RAG Evaluation Using Ragas. Best Practices RAG with Milvus vector… | by Christy Bergman
21 March 2024, Towards Data Science

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