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DBMS > Atos Standard Common Repository vs. Databend vs. Dgraph vs. Spark SQL

System Properties Comparison Atos Standard Common Repository vs. Databend vs. Dgraph vs. Spark SQL

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonDatabend  Xexclude from comparisonDgraph  Xexclude from comparisonSpark SQL  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 networksAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityDistributed and scalable native Graph DBMSSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Relational DBMSGraph DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.34
Rank#283  Overall
#130  Relational DBMS
Score1.53
Rank#152  Overall
#15  Graph DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorygithub.com/­datafuselabs/­databend
www.databend.com
dgraph.iospark.apache.org/­sql
Technical documentationdocs.databend.comdgraph.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAtos Convergence CreatorsDatabend LabsDgraph Labs, Inc.Apache Software Foundation
Initial release2016202120162014
Current release17031.0.59, April 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaRustGoScala
Server operating systemsLinuxhosted
Linux
macOS
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeSchema and schema-less with LDAP viewsyesschema-freeyes
Typing infopredefined data types such as float or dateoptionalyesyesyes
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 indexesyesnoyesno
SQL infoSupport of SQLnoyesnoSQL-like DML and DDL statements
APIs and other access methodsLDAPCLI Client
JDBC
RESTful HTTP API
GraphQL query language
gRPC (using protocol buffers) API
HTTP API
JDBC
ODBC
Supported programming languagesAll languages with LDAP bindingsGo
Java
JavaScript (Node.js)
Python
Rust
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnononono
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionnoneyesyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneSynchronous replication via Raftnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsyesACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlLDAP bind authenticationUsers with fine-grained authorization concept, user rolesno infoPlanned for future releasesno

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Atos Standard Common RepositoryDatabendDgraphSpark SQL
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