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

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

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonHypertable  Xexclude from comparisonSpark SQL  Xexclude from comparisonTigerGraph  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksAn open source BigTable implementation based on distributed file systems such as HadoopSpark 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 modelDocument store
Key-value store
Wide column storeRelational DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score1.83
Rank#139  Overall
#13  Graph DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositoryspark.apache.org/­sqlwww.tigergraph.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.tigergraph.com
DeveloperAtos Convergence CreatorsHypertable Inc.Apache Software Foundation
Initial release2016200920142017
Current release17030.9.8.11, March 20163.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoGNU version 3. Commercial license availableOpen 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 languageJavaC++ScalaC++
Server operating systemsLinuxLinux
OS X
Windows infoan inofficial Windows port is available
Linux
OS X
Windows
Linux
Data schemeSchema and schema-less with LDAP viewsschema-freeyesyes
Typing infopredefined data types such as float or dateoptionalnoyesyes
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
Secondary indexesyesrestricted infoonly exact value or prefix value scansno
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsSQL-like query language (GSQL)
APIs and other access methodsLDAPC++ API
Thrift
JDBC
ODBC
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesAll languages with LDAP bindingsC++
Java
Perl
PHP
Python
Ruby
Java
Python
R
Scala
C++
Java
Server-side scripts infoStored proceduresnononoyes
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factor on file system levelnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynononoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsnonoACID
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.yesnono
User concepts infoAccess controlLDAP bind authenticationnonoRole-based access control

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Atos Standard Common RepositoryHypertableSpark SQLTigerGraph
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