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DBMS > Elasticsearch vs. Firebase Realtime Database vs. Milvus vs. Solr

System Properties Comparison Elasticsearch vs. Firebase Realtime Database vs. Milvus vs. Solr

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Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonMilvus  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.A DBMS designed for efficient storage of vector data and vector similarity searchesA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelSearch engineDocument storeVector DBMSSearch engine
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score135.35
Rank#7  Overall
#1  Search engines
Score14.29
Rank#39  Overall
#6  Document stores
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websitewww.elastic.co/­elasticsearchfirebase.google.com/­products/­realtime-databasemilvus.iosolr.apache.org
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlfirebase.google.com/­docs/­databasemilvus.io/­docs/­overview.mdsolr.apache.org/­resources.html
DeveloperElasticGoogle infoacquired by Google 2014Apache Software Foundation
Initial release2010201220192006
Current release8.6, January 20232.3.4, January 20249.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoElastic LicensecommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenoyesnono
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++, GoJava
Server operating systemsAll OS with a Java VMhostedLinux
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 infoFlexible type definitions. Once a type is defined, it is persistentschema-freeyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesVector, 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.nononoyes
Secondary indexesyes infoAll search fields are automatically indexedyesnoyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like query languagenonoSolr Parallel SQL Interface
APIs and other access methodsJava API
RESTful HTTP/JSON API
Android
iOS
JavaScript API
RESTful HTTP API
RESTful HTTP APIJava API
RESTful HTTP/JSON API
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
Java
JavaScript
Objective-C
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 proceduresyeslimited functionality with using 'rules'noJava plugins
Triggersyes infoby using the 'percolation' featureCallbacks are triggered when data changesnoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop Connectornonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Eventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnooptimistic 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.Memcached and Redis integrationyesyes
User concepts infoAccess controlyes, based on authentication and database rulesRole based access control and fine grained access rightsyes
More information provided by the system vendor
ElasticsearchFirebase Realtime DatabaseMilvusSolr
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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ElasticsearchFirebase Realtime DatabaseMilvusSolr
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