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DBMS > Atos Standard Common Repository vs. BaseX vs. Elasticsearch vs. Google Cloud Bigtable vs. TigerGraph

System Properties Comparison Atos Standard Common Repository vs. BaseX vs. Elasticsearch vs. Google Cloud Bigtable vs. TigerGraph

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonBaseX  Xexclude from comparisonElasticsearch  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonTigerGraph  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 networksLight-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.A 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 metricGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelDocument store
Key-value store
Native XML DBMSSearch engineKey-value store
Wide column store
Graph DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.73
Rank#142  Overall
#4  Native XML DBMS
Score135.35
Rank#7  Overall
#1  Search engines
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score1.83
Rank#139  Overall
#13  Graph DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorybasex.orgwww.elastic.co/­elasticsearchcloud.google.com/­bigtablewww.tigergraph.com
Technical documentationdocs.basex.orgwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlcloud.google.com/­bigtable/­docsdocs.tigergraph.com
DeveloperAtos Convergence CreatorsBaseX GmbHElasticGoogle
Initial release20162007201020152017
Current release170310.7, August 20238.6, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoBSD licenseOpen Source infoElastic Licensecommercialcommercial
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 languageJavaJavaJavaC++
Server operating systemsLinuxLinux
OS X
Windows
All OS with a Java VMhostedLinux
Data schemeSchema and schema-less with LDAP viewsschema-freeschema-free infoFlexible type definitions. Once a type is defined, it is persistentschema-freeyes
Typing infopredefined data types such as float or dateoptionalno infoXQuery supports typesyesnoyes
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 indexedno
SQL infoSupport of SQLnonoSQL-like query languagenoSQL-like query language (GSQL)
APIs and other access methodsLDAPJava API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ
Java API
RESTful HTTP/JSON API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesAll languages with LDAP bindingsActionscript
C
C#
Haskell
Java
JavaScript infoNode.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
Server-side scripts infoStored proceduresnoyesyesnoyes
Triggersyesyes infovia eventsyes infoby using the 'percolation' featurenono
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneyesInternal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoES-Hadoop Connectoryesyes
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 consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integritynonononoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsmultiple readers, single writernoAtomic single-row operationsACID
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 authenticationUsers with fine-grained authorization concept on 4 levelsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access control

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More resources
Atos Standard Common RepositoryBaseXElasticsearchGoogle Cloud BigtableTigerGraph
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