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DBMS > Apache Impala vs. Atos Standard Common Repository vs. Microsoft Access vs. Microsoft Azure AI Search vs. Solr

System Properties Comparison Apache Impala vs. Atos Standard Common Repository vs. Microsoft Access vs. Microsoft Azure AI Search vs. Solr

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSolr  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 networksMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)Search-as-a-service for web and mobile app developmentA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSDocument store
Key-value store
Relational DBMSSearch engineSearch engine
Secondary database modelsDocument storeVector DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.03
Rank#40  Overall
#24  Relational DBMS
Score105.40
Rank#11  Overall
#8  Relational DBMS
Score5.71
Rank#64  Overall
#8  Search engines
Score44.28
Rank#24  Overall
#3  Search engines
Websiteimpala.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.microsoft.com/­en-us/­microsoft-365/­accessazure.microsoft.com/­en-us/­services/­searchsolr.apache.org
Technical documentationimpala.apache.org/­impala-docs.htmldeveloper.microsoft.com/­en-us/­accesslearn.microsoft.com/­en-us/­azure/­searchsolr.apache.org/­resources.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaAtos Convergence CreatorsMicrosoftMicrosoftApache Software Foundation
Initial release20132016199220152006
Current release4.1.0, June 202217031902 (16.0.11328.20222), March 2019V19.5.0, February 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial infoBundled with Microsoft OfficecommercialOpen Source infoApache Version 2
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++Java
Server operating systemsLinuxLinuxWindows infoNot a real database server, but making use of DLLshostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesSchema and schema-less with LDAP viewsyesyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesoptionalyesyesyes infosupports customizable data types and automatic typing
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
Secondary indexesyesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes infobut not compliant to any SQL standardnoSolr Parallel SQL Interface
APIs and other access methodsJDBC
ODBC
LDAPADO.NET
DAO
ODBC
OLE DB
RESTful HTTP APIJava API
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBCAll languages with LDAP bindingsC
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
C#
Java
JavaScript
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes infosince Access 2010 using the ACE-enginenoJava plugins
Triggersnoyesyes infosince Access 2010 using the ACE-enginenoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infocell divisionnoneSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesnoneyes infoImplicit feature of the cloud serviceyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsACID infobut no files for transaction loggingnooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infobut no files for transaction loggingyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosLDAP bind authenticationno infoa simple user-level security was built in till version Access 2003yes infousing Azure authenticationyes

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More resources
Apache ImpalaAtos Standard Common RepositoryMicrosoft AccessMicrosoft Azure AI SearchSolr
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