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DBMS > Apache Impala vs. Atos Standard Common Repository vs. Microsoft Azure AI Search vs. Postgres-XL vs. Warp 10

System Properties Comparison Apache Impala vs. Atos Standard Common Repository vs. Microsoft Azure AI Search vs. Postgres-XL vs. Warp 10

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonPostgres-XL  Xexclude from comparisonWarp 10  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 developmentBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelRelational DBMSDocument store
Key-value store
Search engineRelational DBMSTime Series 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
Score0.49
Rank#256  Overall
#117  Relational DBMS
Score0.07
Rank#349  Overall
#32  Time Series DBMS
Websiteimpala.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositoryazure.microsoft.com/­en-us/­services/­searchwww.postgres-xl.orgwww.warp10.io
Technical documentationimpala.apache.org/­impala-docs.htmllearn.microsoft.com/­en-us/­azure/­searchwww.postgres-xl.org/­documentationwww.warp10.io/­content/­02_Getting_started
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaAtos Convergence CreatorsMicrosoftSenX
Initial release2013201620152014 infosince 2012, originally named StormDB2015
Current release4.1.0, June 20221703V110 R1, October 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialOpen Source infoMozilla public licenseOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaCJava
Server operating systemsLinuxLinuxhostedLinux
macOS
Linux
OS X
Windows
Data schemeyesSchema and schema-less with LDAP viewsyesyesschema-free
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.noyesnoyes infoXML type, but no XML query functionalityno
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoyes infodistributed, parallel query executionno
APIs and other access methodsJDBC
ODBC
LDAPRESTful HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP API
Jupyter
WebSocket
Supported programming languagesAll languages supporting JDBC/ODBCAll languages with LDAP bindingsC#
Java
JavaScript
Python
.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-reducenonouser defined functionsyes infoWarpScript
Triggersnoyesnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infocell divisionSharding infoImplicit feature of the cloud servicehorizontal partitioningSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesyes infoImplicit feature of the cloud serviceselectable replication factor infobased on HBase
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 infobased on HBase
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsnoACID infoMVCCno
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.noyesnonoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosLDAP bind authenticationyes infousing Azure authenticationfine grained access rights according to SQL-standardMandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
Apache ImpalaAtos Standard Common RepositoryMicrosoft Azure AI SearchPostgres-XLWarp 10
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