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

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

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBangdb  Xexclude from comparisonElasticsearch  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopConverged and high performance database for device data, events, time series, document and graphA 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.Search-as-a-service for web and mobile app development
Primary database modelRelational DBMSDocument store
Graph DBMS
Time Series DBMS
Search engineDocument storeSearch engine
Secondary database modelsDocument storeSpatial DBMSDocument store
Spatial DBMS
Vector DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.08
Rank#347  Overall
#47  Document stores
#34  Graph DBMS
#31  Time Series DBMS
Score135.35
Rank#7  Overall
#1  Search engines
Score14.29
Rank#39  Overall
#6  Document stores
Score5.59
Rank#63  Overall
#7  Search engines
Websiteimpala.apache.orgbangdb.comwww.elastic.co/­elasticsearchfirebase.google.com/­products/­realtime-databaseazure.microsoft.com/­en-us/­services/­search
Technical documentationimpala.apache.org/­impala-docs.htmldocs.bangdb.comwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlfirebase.google.com/­docs/­databaselearn.microsoft.com/­en-us/­azure/­search
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaSachin Sinha, BangDBElasticGoogle infoacquired by Google 2014Microsoft
Initial release20132012201020122015
Current release4.1.0, June 2022BangDB 2.0, October 20218.6, January 2023V1
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoBSD 3Open Source infoElastic Licensecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C, C++Java
Server operating systemsLinuxLinuxAll OS with a Java VMhostedhosted
Data schemeyesschema-freeschema-free infoFlexible type definitions. Once a type is defined, it is persistentschema-freeyes
Typing infopredefined data types such as float or dateyesyes: string, long, double, int, geospatial, stream, eventsyesyesyes
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.nonononono
Secondary indexesyesyes infosecondary, composite, nested, reverse, geospatialyes infoAll search fields are automatically indexedyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL like support with command line toolSQL-like query languagenono
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP API
Java API
RESTful HTTP/JSON API
Android
iOS
JavaScript API
RESTful HTTP API
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Java
Python
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
Java
JavaScript
Objective-C
C#
Java
JavaScript
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyeslimited functionality with using 'rules'no
Triggersnoyes, Notifications (with Streaming only)yes infoby using the 'percolation' featureCallbacks are triggered when data changesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factor, Knob for CAP (enterprise version only)yesyes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoES-Hadoop Connectornono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyTunable consistency, set CAP knob accordinglyEventual 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
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoyesno
Concurrency infoSupport for concurrent manipulation of datayesyes, optimistic concurrency controlyesyesyes
Durability infoSupport for making data persistentyesyes, implements WAL (Write ahead log) as wellyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes, run db with in-memory only modeMemcached and Redis integrationno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosyes (enterprise version only)yes, based on authentication and database rulesyes infousing Azure authentication

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More resources
Apache ImpalaBangdbElasticsearchFirebase Realtime DatabaseMicrosoft Azure AI Search
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