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DBMS > AgensGraph vs. Atos Standard Common Repository vs. Spark SQL vs. TigerGraph

System Properties Comparison AgensGraph vs. Atos Standard Common Repository vs. Spark SQL vs. TigerGraph

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Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonSpark SQL  Xexclude from comparisonTigerGraph  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksSpark SQL is a component on top of 'Spark Core' for structured data processingA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelGraph DBMS
Relational DBMS
Document store
Key-value store
Relational DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.20
Rank#321  Overall
#27  Graph DBMS
#143  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score1.83
Rank#139  Overall
#13  Graph DBMS
Websitebitnine.net/­agensgraphatos.net/en/convergence-creators/portfolio/standard-common-repositoryspark.apache.org/­sqlwww.tigergraph.com
Technical documentationbitnine.net/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.tigergraph.com
DeveloperBitnine Global Inc.Atos Convergence CreatorsApache Software Foundation
Initial release2016201620142017
Current release2.1, December 201817033.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercialOpen Source infoApache 2.0commercial
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 languageCJavaScalaC++
Server operating systemsLinux
OS X
Windows
LinuxLinux
OS X
Windows
Linux
Data schemedepending on used data modelSchema and schema-less with LDAP viewsyesyes
Typing infopredefined data types such as float or dateyesoptionalyesyes
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.noyesnono
Secondary indexesyesyesno
SQL infoSupport of SQLyesnoSQL-like DML and DDL statementsSQL-like query language (GSQL)
APIs and other access methodsCypher Query Language
JDBC
LDAPJDBC
ODBC
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesC
Java
JavaScript
Python
All languages with LDAP bindingsJava
Python
R
Scala
C++
Java
Server-side scripts infoStored proceduresyesnonoyes
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritanceSharding infocell divisionyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnonoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of specific operationsnoACID
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.noyesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardLDAP bind authenticationnoRole-based access control

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More resources
AgensGraphAtos Standard Common RepositorySpark SQLTigerGraph
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