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DBMS > Ehcache vs. Milvus vs. Quasardb vs. Solr vs. Valentina Server

System Properties Comparison Ehcache vs. Milvus vs. Quasardb vs. Solr vs. Valentina Server

Editorial information provided by DB-Engines
NameEhcache  Xexclude from comparisonMilvus  Xexclude from comparisonQuasardb  Xexclude from comparisonSolr  Xexclude from comparisonValentina Server  Xexclude from comparison
DescriptionA widely adopted Java cache with tiered storage optionsA DBMS designed for efficient storage of vector data and vector similarity searchesDistributed, high-performance timeseries databaseA widely used distributed, scalable search engine based on Apache LuceneObject-relational database and reports server
Primary database modelKey-value storeVector DBMSTime Series DBMSSearch engineRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.89
Rank#67  Overall
#8  Key-value stores
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score0.17
Rank#327  Overall
#145  Relational DBMS
Websitewww.ehcache.orgmilvus.ioquasar.aisolr.apache.orgwww.valentina-db.net
Technical documentationwww.ehcache.org/­documentationmilvus.io/­docs/­overview.mddoc.quasar.ai/­mastersolr.apache.org/­resources.htmlvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperTerracotta Inc, owned by Software AGquasardbApache Software FoundationParadigma Software
Initial release20092019200920061999
Current release3.10.0, March 20222.3.4, January 20243.14.1, January 20249.6.0, April 20245.7.5
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache Version 2.0commercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenonononono
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 languageJavaC++, GoC++Java
Server operating systemsAll OS with a Java VMLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
BSD
Linux
OS X
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 schemeschema-freeschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesVector, Numeric and Stringyes infointeger and binaryyes 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.nononoyes
Secondary indexesnonoyes infowith tagsyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLnonoSQL-like query languageSolr Parallel SQL Interfaceyes
APIs and other access methodsJCacheRESTful HTTP APIHTTP APIJava API
RESTful HTTP/JSON API
ODBC
Supported programming languagesJavaC++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresnononoJava pluginsyes
Triggersyes infoCache Event Listenersnonoyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerShardingSharding infoconsistent hashingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby using Terracotta ServerSource-replica replication with selectable replication factoryes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonowith Hadoop integrationspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable Consistency (Strong, Eventual, Weak)Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infosupports JTA and can work as an XA resourcenoACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing a tiered cache-storage approachyesyes infoby using LevelDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes infoTransient modeyesyes
User concepts infoAccess controlnoRole based access control and fine grained access rightsCryptographically strong user authentication and audit trailyesfine grained access rights according to SQL-standard
More information provided by the system vendor
EhcacheMilvusQuasardbSolrValentina Server
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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EhcacheMilvusQuasardbSolrValentina Server
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