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DBMS > Milvus vs. mSQL vs. OrigoDB vs. Solr vs. WakandaDB

System Properties Comparison Milvus vs. mSQL vs. OrigoDB vs. Solr vs. WakandaDB

Editorial information provided by DB-Engines
NameMilvus  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparisonOrigoDB  Xexclude from comparisonSolr  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionA DBMS designed for efficient storage of vector data and vector similarity searchesmSQL (Mini SQL) is a simple and lightweight RDBMSA fully ACID in-memory object graph databaseA widely used distributed, scalable search engine based on Apache LuceneWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelVector DBMSRelational DBMSDocument store
Object oriented DBMS
Search engineObject oriented DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score1.27
Rank#167  Overall
#77  Relational DBMS
Score0.00
Rank#383  Overall
#53  Document stores
#20  Object oriented DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websitemilvus.iohughestech.com.au/­products/­msqlorigodb.comsolr.apache.orgwakanda.github.io
Technical documentationmilvus.io/­docs/­overview.mdorigodb.com/­docssolr.apache.org/­resources.htmlwakanda.github.io/­doc
DeveloperHughes TechnologiesRobert Friberg et alApache Software FoundationWakanda SAS
Initial release201919942009 infounder the name LiveDB20062012
Current release2.3.4, January 20244.4, October 20219.6.0, April 20242.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree licenses can be providedOpen SourceOpen Source infoApache Version 2Open Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Zilliz Cloud – Cloud-native service for Milvus
Implementation languageC++, GoCC#JavaC++, JavaScript
Server operating systemsLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Linux
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Data schemeyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateVector, Numeric and StringyesUser defined using .NET types and collectionsyes infosupports customizable data types and automatic typingyes
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 infocan be achieved using .NETyesno
Secondary indexesnoyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnoA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggersnoSolr Parallel SQL Interfaceno
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
.NET Client API
HTTP API
LINQ
Java API
RESTful HTTP/JSON API
RESTful HTTP API
Supported programming languagesC++
Go
Java
JavaScript (Node.js)
Python
C
C++
Delphi
Java
Perl
PHP
Tcl
.Net.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
JavaScript
Server-side scripts infoStored proceduresnonoyesJava pluginsyes
Triggersnonoyes infoDomain Eventsyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesShardingnonehorizontal partitioning infoclient side managed; servers are not synchronizedShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
noneEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonodepending on modelno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesnoyesyesyes
Durability infoSupport for making data persistentyesyesyes infoWrite ahead logyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyesno
User concepts infoAccess controlRole based access control and fine grained access rightsnoRole based authorizationyesyes
More information provided by the system vendor
MilvusmSQL infoMini SQLOrigoDBSolrWakandaDB
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
MilvusmSQL infoMini SQLOrigoDBSolrWakandaDB
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