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

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

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Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonHazelcast  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 widely adopted in-memory data gridA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelSearch engineDocument storeKey-value storeSearch engine
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Document store infoJSON support with IMDG 3.12Spatial 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
Score5.97
Rank#57  Overall
#6  Key-value stores
Score42.91
Rank#24  Overall
#3  Search engines
Websitewww.elastic.co/­elasticsearchfirebase.google.com/­products/­realtime-databasehazelcast.comsolr.apache.org
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlfirebase.google.com/­docs/­databasehazelcast.org/­imdg/­docssolr.apache.org/­resources.html
DeveloperElasticGoogle infoacquired by Google 2014HazelcastApache Software Foundation
Initial release2010201220082006
Current release8.6, January 20235.3.6, November 20239.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoElastic LicensecommercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJava
Server operating systemsAll OS with a Java VMhostedAll OS with a Java VMAll 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-freeschema-freeyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesyes 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 infothe object must implement a serialization strategyyes
Secondary indexesyes infoAll search fields are automatically indexedyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like query languagenoSQL-like query languageSolr Parallel SQL Interface
APIs and other access methodsJava API
RESTful HTTP/JSON API
Android
iOS
JavaScript API
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
Java API
RESTful HTTP/JSON API
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
Java
JavaScript
Objective-C
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.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'yes infoEvent Listeners, Executor ServicesJava plugins
Triggersyes infoby using the 'percolation' featureCallbacks are triggered when data changesyes infoEventsyes 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 infoReplicated Mapyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop Connectornoyesspark-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
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesone or two-phase-commit; repeatable reads; read commitedoptimistic 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 controlyes

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More resources
ElasticsearchFirebase Realtime DatabaseHazelcastSolr
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