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DBMS > Atos Standard Common Repository vs. JaguarDB vs. Newts vs. Spark SQL

System Properties Comparison Atos Standard Common Repository vs. JaguarDB vs. Newts vs. Spark SQL

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonJaguarDB  Xexclude from comparisonNewts  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 networksPerformant, highly scalable DBMS for AI and IoT applicationsTime Series DBMS based on CassandraSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Key-value store
Vector DBMS
Time Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.09
Rank#356  Overall
#53  Key-value stores
#13  Vector DBMS
Score0.00
Rank#396  Overall
#42  Time Series DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.jaguardb.comopennms.github.io/­newtsspark.apache.org/­sql
Technical documentationwww.jaguardb.com/­support.htmlgithub.com/­OpenNMS/­newts/­wikispark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAtos Convergence CreatorsDataJaguar, Inc.OpenNMS GroupApache Software Foundation
Initial release2016201520142014
Current release17033.3 July 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoGPL V3.0Open 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

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Implementation languageJavaC++ infothe server part. Clients available in other languagesJavaScala
Server operating systemsLinuxLinuxLinux
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 indexesyesyesnono
SQL infoSupport of SQLnoA subset of ANSI SQL is implemented infobut no views, foreign keys, triggersnoSQL-like DML and DDL statements
APIs and other access methodsLDAPJDBC
ODBC
HTTP REST
Java API
JDBC
ODBC
Supported programming languagesAll languages with LDAP bindingsC
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
JavaJava
Python
R
Scala
Server-side scripts infoStored proceduresnononono
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingSharding infobased on Cassandrayes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replicationselectable replication factor infobased on Cassandranone
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 configurationEventual ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsnonono
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.yesnonono
User concepts infoAccess controlLDAP bind authenticationrights management via user accountsnono

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Atos Standard Common RepositoryJaguarDBNewtsSpark SQL
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