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DBMS > Atos Standard Common Repository vs. Elasticsearch vs. etcd vs. Hypertable vs. Microsoft Azure AI Search

System Properties Comparison Atos Standard Common Repository vs. Elasticsearch vs. etcd vs. Hypertable vs. Microsoft Azure AI Search

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonElasticsearch  Xexclude from comparisonetcd  Xexclude from comparisonHypertable  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionHighly 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 metricA distributed reliable key-value storeAn open source BigTable implementation based on distributed file systems such as HadoopSearch-as-a-service for web and mobile app development
Primary database modelDocument store
Key-value store
Search engineKey-value storeWide column storeSearch engine
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score135.35
Rank#7  Overall
#1  Search engines
Score7.25
Rank#54  Overall
#5  Key-value stores
Score5.59
Rank#63  Overall
#7  Search engines
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.elastic.co/­elasticsearchetcd.io
github.com/­etcd-io/­etcd
azure.microsoft.com/­en-us/­services/­search
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmletcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
learn.microsoft.com/­en-us/­azure/­search
DeveloperAtos Convergence CreatorsElasticHypertable Inc.Microsoft
Initial release2016201020092015
Current release17038.6, January 20233.4, August 20190.9.8.11, March 2016V1
License infoCommercial or Open SourcecommercialOpen Source infoElastic LicenseOpen Source infoApache Version 2.0Open Source infoGNU version 3. Commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaGoC++
Server operating systemsLinuxAll OS with a Java VMFreeBSD
Linux
Windows infoexperimental
Linux
OS X
Windows infoan inofficial Windows port is available
hosted
Data schemeSchema and schema-less with LDAP viewsschema-free infoFlexible type definitions. Once a type is defined, it is persistentschema-freeschema-freeyes
Typing infopredefined data types such as float or dateoptionalyesnonoyes
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.yesnonono
Secondary indexesyesyes infoAll search fields are automatically indexednorestricted infoonly exact value or prefix value scansyes
SQL infoSupport of SQLnoSQL-like query languagenonono
APIs and other access methodsLDAPJava API
RESTful HTTP/JSON API
gRPC
JSON over HTTP
C++ API
Thrift
RESTful HTTP API
Supported programming languagesAll languages with LDAP bindings.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
C++
Java
Perl
PHP
Python
Ruby
C#
Java
JavaScript
Python
Server-side scripts infoStored proceduresnoyesnonono
Triggersyesyes infoby using the 'percolation' featureyes, watching key changesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.selectable replication factor on file system levelyes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop Connectornoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsnononono
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.yesMemcached and Redis integrationnono
User concepts infoAccess controlLDAP bind authenticationnonoyes infousing Azure authentication

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Atos Standard Common RepositoryElasticsearchetcdHypertableMicrosoft Azure AI Search
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