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DBMS > Atos Standard Common Repository vs. BigObject vs. Elasticsearch vs. Microsoft Azure AI Search vs. Splice Machine

System Properties Comparison Atos Standard Common Repository vs. BigObject vs. Elasticsearch vs. Microsoft Azure AI Search vs. Splice Machine

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonBigObject  Xexclude from comparisonElasticsearch  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSplice Machine  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksAnalytic DBMS for real-time computations and queriesA 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 developmentOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument store
Key-value store
Relational DBMS infoa hierachical model (tree) can be imposedSearch engineSearch engineRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score135.35
Rank#7  Overall
#1  Search engines
Score5.59
Rank#63  Overall
#7  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorybigobject.iowww.elastic.co/­elasticsearchazure.microsoft.com/­en-us/­services/­searchsplicemachine.com
Technical documentationdocs.bigobject.iowww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmllearn.microsoft.com/­en-us/­azure/­searchsplicemachine.com/­how-it-works
DeveloperAtos Convergence CreatorsBigObject, Inc.ElasticMicrosoftSplice Machine
Initial release20162015201020152014
Current release17038.6, January 2023V13.1, March 2021
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availableOpen Source infoElastic LicensecommercialOpen Source infoAGPL 3.0, commercial license available
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 languageJavaJavaJava
Server operating systemsLinuxLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
All OS with a Java VMhostedLinux
OS X
Solaris
Windows
Data schemeSchema and schema-less with LDAP viewsyesschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesyes
Typing infopredefined data types such as float or dateoptionalyesyesyesyes
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 indexesyesyesyes infoAll search fields are automatically indexedyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsSQL-like query languagenoyes
APIs and other access methodsLDAPfluentd
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
RESTful HTTP APIJDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages with LDAP bindings.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C#
Java
JavaScript
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoLuayesnoyes infoJava
Triggersyesnoyes infoby using the 'percolation' featurenoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionnoneShardingSharding infoImplicit feature of the cloud serviceShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneyesyes infoImplicit feature of the cloud serviceMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoES-Hadoop ConnectornoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationnoneEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infoautomatically between fact table and dimension tablesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsnononoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yesyesyes, multi-version concurrency control (MVCC)
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.yesyesMemcached and Redis integrationnoyes
User concepts infoAccess controlLDAP bind authenticationnoyes infousing Azure authenticationAccess rights for users, groups and roles according to SQL-standard

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More resources
Atos Standard Common RepositoryBigObjectElasticsearchMicrosoft Azure AI SearchSplice Machine
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