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DBMS > FoundationDB vs. Linter vs. Milvus vs. Solr

System Properties Comparison FoundationDB vs. Linter vs. Milvus vs. Solr

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Editorial information provided by DB-Engines
NameFoundationDB  Xexclude from comparisonLinter  Xexclude from comparisonMilvus  Xexclude from comparisonSolr  Xexclude from comparison
Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.
DescriptionOrdered key-value store. Core features are complimented by layers.RDBMS for high security requirementsA DBMS designed for efficient storage of vector data and vector similarity searchesA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Relational DBMSVector DBMSSearch engine
Secondary database modelsSpatial DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.50
Rank#166  Overall
#29  Document stores
#27  Key-value stores
#76  Relational DBMS
Score0.15
Rank#339  Overall
#147  Relational DBMS
Score1.70
Rank#150  Overall
#5  Vector DBMS
Score43.91
Rank#24  Overall
#3  Search engines
Websitegithub.com/­apple/­foundationdblinter.rumilvus.iosolr.apache.org
Technical documentationapple.github.io/­foundationdbmilvus.io/­docs/­overview.mdsolr.apache.org/­resources.html
DeveloperFoundationDBrelex.ruApache Software Foundation
Initial release2013199020192006
Current release6.2.28, November 20202.3.4, January 20249.5.0, February 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache Version 2.0Open Source infoApache Version 2
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 and C++C++, GoJava
Server operating systemsLinux
OS X
Windows
AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Linux
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 schemeschema-free infosome layers support schemasyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateno infosome layers support typingyesVector, Numeric and Stringyes infosupports customizable data types and automatic typing
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.nonoyes
Secondary indexesnoyesnoyes infoAll search fields are automatically indexed
SQL infoSupport of SQLsupported in specific SQL layer onlyyesnoSolr Parallel SQL Interface
APIs and other access methodsADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
RESTful HTTP APIJava API
RESTful HTTP/JSON API
Supported programming languages.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
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
Server-side scripts infoStored proceduresin SQL-layer onlyyes infoproprietary syntax with the possibility to convert from PL/SQLnoJava plugins
Triggersnoyesnoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemLinearizable consistencyImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Eventual Consistency
Foreign keys infoReferential integrityin SQL-layer onlyyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnooptimistic locking
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.yesyes
User concepts infoAccess controlnofine grained access rights according to SQL-standardRole based access control and fine grained access rightsyes
More information provided by the system vendor
FoundationDBLinterMilvusSolr
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
FoundationDBLinterMilvusSolr
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