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DBMS > GridDB vs. Milvus vs. Qdrant

System Properties Comparison GridDB vs. Milvus vs. Qdrant

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonMilvus  Xexclude from comparisonQdrant  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataA DBMS designed for efficient storage of vector data and vector similarity searchesA high-performance vector database with neural network or semantic-based matching
Primary database modelTime Series DBMSVector DBMSVector DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score1.16
Rank#175  Overall
#6  Vector DBMS
Websitegriddb.netmilvus.iogithub.com/­qdrant/­qdrant
qdrant.tech
Technical documentationdocs.griddb.netmilvus.io/­docs/­overview.mdqdrant.tech/­documentation
DeveloperToshiba CorporationQdrant
Initial release201320192021
Current release5.1, August 20222.3.4, January 2024
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonono
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++C++, GoRust
Server operating systemsLinuxLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Docker
Linux
macOS
Windows
Data schemeyesschema-free
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampVector, Numeric and StringNumbers, Strings, Geo, Boolean
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.nonono
Secondary indexesyesnoyes infoKeywords, numberic ranges, geo, full-text
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)nono
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
RESTful HTTP APIgRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresnono
Triggersyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationCollection-level replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Eventual Consistency, tunable consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlAccess rights for users can be defined per databaseRole based access control and fine grained access rightsKey-based authentication
More information provided by the system vendor
GridDBMilvusQdrant
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Milvus is an open-source and cloud-native vector database built for production-ready...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Highly available, versatile, and robust with millisecond latency. Supports batch...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
RAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Milvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
Market metricsGitHub trending repository
» more
As of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
Milvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
GridDBMilvusQdrant
DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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Toshiba's Distributed Database GridDB(R) Now Features Scale-Out and Scale-Up combo for Petabyte-scale Data ...
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