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DBMS > Apache Impala vs. Atos Standard Common Repository vs. Elasticsearch vs. Microsoft Azure AI Search vs. Riak TS

System Properties Comparison Apache Impala vs. Atos Standard Common Repository vs. Elasticsearch vs. Microsoft Azure AI Search vs. Riak TS

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonElasticsearch  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonRiak TS  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 networksA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricSearch-as-a-service for web and mobile app developmentRiak TS is a distributed NoSQL database optimized for time series data and based on Riak KV
Primary database modelRelational DBMSDocument store
Key-value store
Search engineSearch engineTime Series DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
Vector DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score135.35
Rank#7  Overall
#1  Search engines
Score5.59
Rank#63  Overall
#7  Search engines
Score0.20
Rank#319  Overall
#27  Time Series DBMS
Websiteimpala.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.elastic.co/­elasticsearchazure.microsoft.com/­en-us/­services/­search
Technical documentationimpala.apache.org/­impala-docs.htmlwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmllearn.microsoft.com/­en-us/­azure/­searchwww.tiot.jp/­riak-docs/­riak/­ts/­latest
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaAtos Convergence CreatorsElasticMicrosoftOpen Source, formerly Basho Technologies
Initial release20132016201020152015
Current release4.1.0, June 202217038.6, January 2023V13.0.0, September 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoElastic LicensecommercialOpen Source
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++JavaJavaErlang
Server operating systemsLinuxLinuxAll OS with a Java VMhostedLinux
OS X
Data schemeyesSchema and schema-less with LDAP viewsschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesschema-free
Typing infopredefined data types such as float or dateyesoptionalyesyesno
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.noyesnonono
Secondary indexesyesyesyes infoAll search fields are automatically indexedyesrestricted
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like query languagenoyes, limited
APIs and other access methodsJDBC
ODBC
LDAPJava API
RESTful HTTP/JSON API
RESTful HTTP APIHTTP API
Native Erlang Interface
Supported programming languagesAll languages supporting JDBC/ODBCAll languages with LDAP bindings.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C#
Java
JavaScript
Python
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyesnoErlang
Triggersnoyesyes infoby using the 'percolation' featurenoyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infocell divisionShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesyesyes infoImplicit feature of the cloud serviceselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceES-Hadoop Connectornoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonononono infolinks between datasets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsnonono
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.noyesMemcached and Redis integrationno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosLDAP bind authenticationyes infousing Azure authenticationno

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More resources
Apache ImpalaAtos Standard Common RepositoryElasticsearchMicrosoft Azure AI SearchRiak TS
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