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DBMS > Apache Impala vs. Atos Standard Common Repository vs. Microsoft Azure AI Search vs. Microsoft Azure Table Storage vs. Postgres-XL

System Properties Comparison Apache Impala vs. Atos Standard Common Repository vs. Microsoft Azure AI Search vs. Microsoft Azure Table Storage vs. Postgres-XL

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonPostgres-XL  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 networksSearch-as-a-service for web and mobile app developmentA Wide Column Store for rapid development using massive semi-structured datasetsBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelRelational DBMSDocument store
Key-value store
Search engineWide column storeRelational DBMS
Secondary database modelsDocument storeVector DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Score4.48
Rank#75  Overall
#6  Wide column stores
Score0.49
Rank#256  Overall
#117  Relational DBMS
Websiteimpala.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositoryazure.microsoft.com/­en-us/­services/­searchazure.microsoft.com/­en-us/­services/­storage/­tableswww.postgres-xl.org
Technical documentationimpala.apache.org/­impala-docs.htmllearn.microsoft.com/­en-us/­azure/­searchwww.postgres-xl.org/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaAtos Convergence CreatorsMicrosoftMicrosoft
Initial release20132016201520122014 infosince 2012, originally named StormDB
Current release4.1.0, June 20221703V110 R1, October 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialcommercialOpen Source infoMozilla public license
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC
Server operating systemsLinuxLinuxhostedhostedLinux
macOS
Data schemeyesSchema and schema-less with LDAP viewsyesschema-freeyes
Typing infopredefined data types such as float or dateyesoptionalyesyesyes
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.noyesnonoyes infoXML type, but no XML query functionality
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnononoyes infodistributed, parallel query execution
APIs and other access methodsJDBC
ODBC
LDAPRESTful HTTP APIRESTful HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesAll languages supporting JDBC/ODBCAll languages with LDAP bindingsC#
Java
JavaScript
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenononouser defined functions
Triggersnoyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infocell divisionSharding infoImplicit feature of the cloud serviceSharding infoImplicit feature of the cloud servicehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesyes infoImplicit feature of the cloud serviceyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsnooptimistic lockingACID infoMVCC
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.noyesnonono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosLDAP bind authenticationyes infousing Azure authenticationAccess rights based on private key authentication or shared access signaturesfine grained access rights according to SQL-standard

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More resources
Apache ImpalaAtos Standard Common RepositoryMicrosoft Azure AI SearchMicrosoft Azure Table StoragePostgres-XL
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