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DBMS > Apache Impala vs. Atos Standard Common Repository vs. IBM Db2 Event Store vs. Microsoft Azure AI Search vs. Postgres-XL

System Properties Comparison Apache Impala vs. Atos Standard Common Repository vs. IBM Db2 Event Store vs. Microsoft Azure AI Search vs. Postgres-XL

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonMicrosoft Azure AI Search  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 networksDistributed Event Store optimized for Internet of Things use casesSearch-as-a-service for web and mobile app developmentBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelRelational DBMSDocument store
Key-value store
Event Store
Time Series DBMS
Search engineRelational 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
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Score0.49
Rank#256  Overall
#117  Relational DBMS
Websiteimpala.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.ibm.com/­products/­db2-event-storeazure.microsoft.com/­en-us/­services/­searchwww.postgres-xl.org
Technical documentationimpala.apache.org/­impala-docs.htmlwww.ibm.com/­docs/­en/­db2-event-storelearn.microsoft.com/­en-us/­azure/­searchwww.postgres-xl.org/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaAtos Convergence CreatorsIBMMicrosoft
Initial release20132016201720152014 infosince 2012, originally named StormDB
Current release4.1.0, June 202217032.0V110 R1, October 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial infofree developer edition availablecommercialOpen Source infoMozilla public license
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC and C++C
Server operating systemsLinuxLinuxLinux infoLinux, macOS, Windows for the developer additionhostedLinux
macOS
Data schemeyesSchema and schema-less with LDAP viewsyesyesyes
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 indexesyesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes infothrough the embedded Spark runtimenoyes infodistributed, parallel query execution
APIs and other access methodsJDBC
ODBC
LDAPADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
RESTful HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesAll languages supporting JDBC/ODBCAll languages with LDAP bindingsC
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
C#
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-reducenoyesnouser defined functions
Triggersnoyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infocell divisionShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesActive-active shard replicationyes infoImplicit feature of the cloud service
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 configurationEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsnonoACID infoMVCC
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableyesyes
Durability infoSupport for making data persistentyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesnono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosLDAP bind authenticationfine grained access rights according to SQL-standardyes infousing Azure authenticationfine grained access rights according to SQL-standard

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More resources
Apache ImpalaAtos Standard Common RepositoryIBM Db2 Event StoreMicrosoft Azure AI SearchPostgres-XL
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