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DBMS > Amazon CloudSearch vs. Milvus vs. Solr vs. Teradata

System Properties Comparison Amazon CloudSearch vs. Milvus vs. Solr vs. Teradata

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Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonMilvus  Xexclude from comparisonSolr  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionA hosted search engine service by Amazon with the data stored in Amazons cloudA DBMS designed for efficient storage of vector data and vector similarity searchesA widely used distributed, scalable search engine based on Apache LuceneA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelSearch engineVector DBMSSearch engineRelational DBMS
Secondary database modelsSpatial DBMSDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.85
Rank#137  Overall
#12  Search engines
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websiteaws.amazon.com/­cloudsearchmilvus.iosolr.apache.orgwww.teradata.com
Technical documentationdocs.aws.amazon.com/­cloudsearchmilvus.io/­docs/­overview.mdsolr.apache.org/­resources.htmldocs.teradata.com
DeveloperAmazonApache Software FoundationTeradata
Initial release2012201920061984
Current release2.3.4, January 20249.6.0, April 2024Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
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++, GoJava
Server operating systemshostedLinux
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)hosted
Linux
Data schemeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesVector, 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.noyesyes
Secondary indexesyes infoall search fields are automatically indexednoyes infoAll search fields are automatically indexedyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLnonoSolr Parallel SQL Interfaceyes infoSQL 2016 + extensions
APIs and other access methodsHTTP APIRESTful HTTP APIJava API
RESTful HTTP/JSON API
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesC++
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++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresnonoJava pluginsyes infoUDFs, stored procedures, table functions in parallel
Triggersnonoyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requiredShardingShardingSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesyes infomanaged transparently by AWSyesMulti-source replication
Source-replica replication
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 systemBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonooptimistic lockingACID
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.yesyesyes
User concepts infoAccess controlauthentication via encrypted signaturesRole based access control and fine grained access rightsyesfine grained access rights according to SQL-standard
More information provided by the system vendor
Amazon CloudSearchMilvusSolrTeradata
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
Amazon CloudSearchMilvusSolrTeradata
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