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

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

Editorial information provided by DB-Engines
NameFoundationDB  Xexclude from comparisonLinter  Xexclude from comparisonMilvus  Xexclude from comparisonSolr  Xexclude from comparisonVertica infoOpenText™ Vertica™  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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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 LuceneCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Relational DBMSVector DBMSSearch engineRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMSSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.03
Rank#190  Overall
#31  Document stores
#28  Key-value stores
#89  Relational DBMS
Score0.09
Rank#346  Overall
#152  Relational DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitegithub.com/­apple/­foundationdblinter.rumilvus.iosolr.apache.orgwww.vertica.com
Technical documentationapple.github.io/­foundationdbmilvus.io/­docs/­overview.mdsolr.apache.org/­resources.htmlvertica.com/­documentation
DeveloperFoundationDBrelex.ruApache Software FoundationOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20131990201920062005
Current release6.2.28, November 20202.3.4, January 20249.6.0, April 202412.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache Version 2.0Open Source infoApache Version 2commercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
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++, GoJavaC++
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)Linux
Data schemeschema-free infosome layers support schemasyesyes infoDynamic Fields enables on-the-fly addition of new fieldsYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateno infosome layers support typingyesVector, Numeric and Stringyes 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.nonoyesno
Secondary indexesnoyesnoyes infoAll search fields are automatically indexedNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLsupported in specific SQL layer onlyyesnoSolr Parallel SQL InterfaceFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
RESTful HTTP APIJava API
RESTful HTTP/JSON API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
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
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresin SQL-layer onlyyes infoproprietary syntax with the possibility to convert from PL/SQLnoJava pluginsyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyesnoyes infoUser configurable commands triggered on index changesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationyesMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemLinearizable consistencyImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityin SQL-layer onlyyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnooptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlnofine grained access rights according to SQL-standardRole based access control and fine grained access rightsyesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
FoundationDBLinterMilvusSolrVertica infoOpenText™ Vertica™
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
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Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
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Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
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Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersMilvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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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
Cost-based models and subscription-based models are both available. One license is...
» more

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More resources
FoundationDBLinterMilvusSolrVertica infoOpenText™ Vertica™
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