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DBMS > Apache Impala vs. Elasticsearch vs. Firebase Realtime Database vs. GigaSpaces vs. Microsoft Azure AI Search

System Properties Comparison Apache Impala vs. Elasticsearch vs. Firebase Realtime Database vs. GigaSpaces vs. Microsoft Azure AI Search

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonElasticsearch  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGigaSpaces  Xexclude from comparisonMicrosoft Azure AI Search  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.High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsSearch-as-a-service for web and mobile app development
Primary database modelRelational DBMSSearch engineDocument storeDocument store
Object oriented DBMS infoValues are user defined objects
Search engine
Secondary database modelsDocument storeDocument store
Spatial DBMS
Vector DBMS
Graph DBMS
Search engine
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.03
Rank#40  Overall
#24  Relational DBMS
Score134.78
Rank#7  Overall
#1  Search engines
Score15.00
Rank#39  Overall
#6  Document stores
Score1.02
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score5.71
Rank#64  Overall
#8  Search engines
Websiteimpala.apache.orgwww.elastic.co/­elasticsearchfirebase.google.com/­products/­realtime-databasewww.gigaspaces.comazure.microsoft.com/­en-us/­services/­search
Technical documentationimpala.apache.org/­impala-docs.htmlwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlfirebase.google.com/­docs/­databasedocs.gigaspaces.com/­latest/­landing.htmllearn.microsoft.com/­en-us/­azure/­search
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaElasticGoogle infoacquired by Google 2014Gigaspaces TechnologiesMicrosoft
Initial release20132010201220002015
Current release4.1.0, June 20228.6, January 202315.5, September 2020V1
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoElastic LicensecommercialOpen Source infoApache Version 2; Commercial licenses availablecommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaJava, C++, .Net
Server operating systemsLinuxAll OS with a Java VMhostedLinux
macOS
Solaris
Windows
hosted
Data schemeyesschema-free infoFlexible type definitions. Once a type is defined, it is persistentschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nononono infoXML can be used for describing objects metadatano
Secondary indexesyesyes infoAll search fields are automatically indexedyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languagenoSQL-99 for query and DML statementsno
APIs and other access methodsJDBC
ODBC
Java API
RESTful HTTP/JSON API
Android
iOS
JavaScript API
RESTful HTTP API
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
Java
JavaScript
Objective-C
.Net
C++
Java
Python
Scala
C#
Java
JavaScript
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyeslimited functionality with using 'rules'yesno
Triggersnoyes infoby using the 'percolation' featureCallbacks are triggered when data changesyes, event driven architectureno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceES-Hadoop Connectornoyes infoMap-Reduce pattern can be built with XAP task executorsno
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
Immediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoyesACIDno
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.noMemcached and Redis integrationyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosyes, based on authentication and database rulesRole-based access controlyes infousing Azure authentication

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More resources
Apache ImpalaElasticsearchFirebase Realtime DatabaseGigaSpacesMicrosoft Azure AI Search
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