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DBMS > Kinetica vs. Milvus vs. Solr vs. TerarkDB

System Properties Comparison Kinetica vs. Milvus vs. Solr vs. TerarkDB

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonMilvus  Xexclude from comparisonSolr  Xexclude from comparisonTerarkDB  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsA DBMS designed for efficient storage of vector data and vector similarity searchesA widely used distributed, scalable search engine based on Apache LuceneA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelRelational DBMSVector DBMSSearch engineKey-value store
Secondary database modelsSpatial DBMS
Time Series DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.69
Rank#234  Overall
#107  Relational DBMS
Score1.81
Rank#144  Overall
#5  Vector DBMS
Score44.28
Rank#24  Overall
#3  Search engines
Score0.04
Rank#377  Overall
#58  Key-value stores
Websitewww.kinetica.commilvus.iosolr.apache.orggithub.com/­bytedance/­terarkdb
Technical documentationdocs.kinetica.commilvus.io/­docs/­overview.mdsolr.apache.org/­resources.htmlbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperKineticaApache Software FoundationByteDance, originally Terark
Initial release2012201920062016
Current release7.1, August 20212.3.4, January 20249.5.0, February 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2commercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud servicenononono
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++C++, GoJavaC++
Server operating systemsLinuxLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsschema-free
Typing infopredefined data types such as float or dateyesVector, Numeric and Stringyes infosupports customizable data types and automatic typingno
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.nonoyesno
Secondary indexesyesnoyes infoAll search fields are automatically indexedno
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSolr Parallel SQL Interfaceno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP APIJava API
RESTful HTTP/JSON API
C++ API
Java API
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C++
Java
Server-side scripts infoStored proceduresuser defined functionsnoJava pluginsno
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenoyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Eventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonooptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMyesyesyes
User concepts infoAccess controlAccess rights for users and roles on table levelRole based access control and fine grained access rightsyesno
More information provided by the system vendor
KineticaMilvusSolrTerarkDB
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
KineticaMilvusSolrTerarkDB
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