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DBMS > Apache Impala vs. Elasticsearch vs. Firebase Realtime Database vs. Solr

System Properties Comparison Apache Impala vs. Elasticsearch vs. Firebase Realtime Database vs. Solr

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonElasticsearch  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA 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 used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSSearch engineDocument storeSearch engine
Secondary database modelsDocument storeDocument store
Spatial DBMS
Vector DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score135.35
Rank#7  Overall
#1  Search engines
Score14.29
Rank#39  Overall
#6  Document stores
Score42.91
Rank#24  Overall
#3  Search engines
Websiteimpala.apache.orgwww.elastic.co/­elasticsearchfirebase.google.com/­products/­realtime-databasesolr.apache.org
Technical documentationimpala.apache.org/­impala-docs.htmlwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlfirebase.google.com/­docs/­databasesolr.apache.org/­resources.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaElasticGoogle infoacquired by Google 2014Apache Software Foundation
Initial release2013201020122006
Current release4.1.0, June 20228.6, January 20239.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoElastic LicensecommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaJava
Server operating systemsLinuxAll OS with a Java VMhostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesschema-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 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.nononoyes
Secondary indexesyesyes infoAll search fields are automatically indexedyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languagenoSolr Parallel SQL Interface
APIs and other access methodsJDBC
ODBC
Java API
RESTful HTTP/JSON API
Android
iOS
JavaScript API
RESTful HTTP API
Java API
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBC.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
Java
JavaScript
Objective-C
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyeslimited functionality with using 'rules'Java plugins
Triggersnoyes infoby using the 'percolation' featureCallbacks are triggered when data changesyes 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 nodesselectable replication factoryesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceES-Hadoop Connectornospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual 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
Eventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoyesoptimistic 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.noMemcached and Redis integrationyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosyes, based on authentication and database rulesyes

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More resources
Apache ImpalaElasticsearchFirebase Realtime DatabaseSolr
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