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DBMS > Apache Impala vs. Atos Standard Common Repository vs. Microsoft Azure AI Search vs. Oracle Berkeley DB vs. Postgres-XL

System Properties Comparison Apache Impala vs. Atos Standard Common Repository vs. Microsoft Azure AI Search vs. Oracle Berkeley DB 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 comparisonOracle Berkeley DB  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 developmentWidely used in-process key-value storeBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelRelational DBMSDocument store
Key-value store
Search engineKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational 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
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Websiteimpala.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositoryazure.microsoft.com/­en-us/­services/­searchwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlwww.postgres-xl.org
Technical documentationimpala.apache.org/­impala-docs.htmllearn.microsoft.com/­en-us/­azure/­searchdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlwww.postgres-xl.org/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaAtos Convergence CreatorsMicrosoftOracle infooriginally developed by Sleepycat, which was acquired by Oracle
Initial release20132016201519942014 infosince 2012, originally named StormDB
Current release4.1.0, June 20221703V118.1.40, May 202010 R1, October 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialOpen Source infocommercial license availableOpen Source infoMozilla public license
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++JavaC, Java, C++ (depending on the Berkeley DB edition)C
Server operating systemsLinuxLinuxhostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
macOS
Data schemeyesSchema and schema-less with LDAP viewsyesschema-freeyes
Typing infopredefined data types such as float or dateyesoptionalyesnoyes
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 infoonly with the Berkeley DB XML editionyes infoXML type, but no XML query functionality
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoyes infoSQL interfaced based on SQLite is availableyes infodistributed, parallel query execution
APIs and other access methodsJDBC
ODBC
LDAPRESTful 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 infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
.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
Triggersnoyesnoyes infoonly for the SQL APIyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infocell divisionSharding infoImplicit feature of the cloud servicenonehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesyes infoImplicit feature of the cloud serviceSource-replica replication
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 Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsnoACIDACID infoMVCC
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.noyesnoyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosLDAP bind authenticationyes infousing Azure authenticationnofine grained access rights according to SQL-standard

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More resources
Apache ImpalaAtos Standard Common RepositoryMicrosoft Azure AI SearchOracle Berkeley DBPostgres-XL
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