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DBMS > Atos Standard Common Repository vs. DolphinDB vs. Spark SQL

System Properties Comparison Atos Standard Common Repository vs. DolphinDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonDolphinDB  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 networksDolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Time Series DBMSRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.13
Rank#80  Overall
#6  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.dolphindb.comspark.apache.org/­sql
Technical documentationdocs.dolphindb.cn/­en/­help200/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAtos Convergence CreatorsDolphinDB, IncApache Software Foundation
Initial release201620182014
Current release1703v2.00.4, January 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercial infofree community version availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++Scala
Server operating systemsLinuxLinux
Windows
Linux
OS X
Windows
Data schemeSchema and schema-less with LDAP viewsyesyes
Typing infopredefined data types such as float or dateoptionalyesyes
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 indexesyesyesno
SQL infoSupport of SQLnoSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsLDAPJDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
JDBC
ODBC
Supported programming languagesAll languages with LDAP bindingsC#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyesno
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionhorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsyesno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlLDAP bind authenticationAdministrators, Users, Groupsno

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More resources
Atos Standard Common RepositoryDolphinDBSpark SQL
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