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DBMS > Atos Standard Common Repository vs. HugeGraph vs. Prometheus vs. Spark SQL

System Properties Comparison Atos Standard Common Repository vs. HugeGraph vs. Prometheus vs. Spark SQL

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonHugeGraph  Xexclude from comparisonPrometheus  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 networksA fast-speed and highly-scalable Graph DBMSOpen-source Time Series DBMS and monitoring systemSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Graph DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorygithub.com/­hugegraph
hugegraph.apache.org
prometheus.iospark.apache.org/­sql
Technical documentationhugegraph.apache.org/­docsprometheus.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAtos Convergence CreatorsBaiduApache Software Foundation
Initial release2016201820152014
Current release17030.93.5.0 ( 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 languageJavaJavaGoScala
Server operating systemsLinuxLinux
macOS
Unix
Linux
Windows
Linux
OS X
Windows
Data schemeSchema and schema-less with LDAP viewsyesyesyes
Typing infopredefined data types such as float or dateoptionalyesNumeric data onlyyes
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.yesnono infoImport of XML data possibleno
Secondary indexesyesyes infoalso supports composite index and range indexnono
SQL infoSupport of SQLnononoSQL-like DML and DDL statements
APIs and other access methodsLDAPJava API
RESTful HTTP API
TinkerPop Gremlin
RESTful HTTP/JSON APIJDBC
ODBC
Supported programming languagesAll languages with LDAP bindingsGroovy
Java
Python
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoasynchronous Gremlin script jobsnono
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionyes infodepending on used storage backend, e.g. Cassandra and HBaseShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infodepending on used storage backend, e.g. Cassandra and HBaseyes infoby Federationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsvia hugegraph-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual Consistencynone
Foreign keys infoReferential integritynoyes infoedges in graphnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDnono
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.yesyesnono
User concepts infoAccess controlLDAP bind authenticationUsers, roles and permissionsnono

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Atos Standard Common RepositoryHugeGraphPrometheusSpark SQL
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