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DBMS > Apache Impala vs. Atos Standard Common Repository vs. Elasticsearch vs. GridDB vs. Microsoft Azure AI Search

System Properties Comparison Apache Impala vs. Atos Standard Common Repository vs. Elasticsearch vs. GridDB vs. Microsoft Azure AI Search

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonElasticsearch  Xexclude from comparisonGridDB  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionAnalytic DBMS for HadoopHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksA 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 metricScalable in-memory time series database optimized for IoT and Big DataSearch-as-a-service for web and mobile app development
Primary database modelRelational DBMSDocument store
Key-value store
Search engineTime Series DBMSSearch engine
Secondary database modelsDocument storeDocument store
Spatial DBMS
Vector DBMS
Key-value store
Relational DBMS
Vector 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
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Websiteimpala.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.elastic.co/­elasticsearchgriddb.netazure.microsoft.com/­en-us/­services/­search
Technical documentationimpala.apache.org/­impala-docs.htmlwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.griddb.netlearn.microsoft.com/­en-us/­azure/­search
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaAtos Convergence CreatorsElasticToshiba CorporationMicrosoft
Initial release20132016201020132015
Current release4.1.0, June 202217038.6, January 20235.1, August 2022V1
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoElastic LicenseOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaJavaC++
Server operating systemsLinuxLinuxAll OS with a Java VMLinuxhosted
Data schemeyesSchema and schema-less with LDAP viewsschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesyes
Typing infopredefined data types such as float or dateyesoptionalyesyes infonumerical, string, blob, geometry, boolean, timestampyes
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.noyesnonono
Secondary indexesyesyesyes infoAll search fields are automatically indexedyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like query languageSQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methodsJDBC
ODBC
LDAPJava API
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCAll languages with LDAP bindings.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
Java
JavaScript
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyesnono
Triggersnoyesyes infoby using the 'percolation' featureyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infocell divisionShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesyesSource-replica replicationyes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceES-Hadoop ConnectorConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsnoACID at container levelno
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.noyesMemcached and Redis integrationyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosLDAP bind authenticationAccess rights for users can be defined per databaseyes infousing Azure authentication
More information provided by the system vendor
Apache ImpalaAtos Standard Common RepositoryElasticsearchGridDBMicrosoft Azure AI Search
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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Apache ImpalaAtos Standard Common RepositoryElasticsearchGridDBMicrosoft Azure AI Search
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