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DBMS > Atos Standard Common Repository vs. LevelDB vs. SpaceTime vs. Spark SQL

System Properties Comparison Atos Standard Common Repository vs. LevelDB vs. SpaceTime vs. Spark SQL

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonLevelDB  Xexclude from comparisonSpaceTime  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 networksEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesSpaceTime is a spatio-temporal DBMS with a focus on performance.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Key-value storeSpatial DBMSRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.75
Rank#107  Overall
#19  Key-value stores
Score0.00
Rank#396  Overall
#8  Spatial DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorygithub.com/­google/­leveldbwww.mireo.com/­spacetimespark.apache.org/­sql
Technical documentationgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAtos Convergence CreatorsGoogleMireoApache Software Foundation
Initial release2016201120202014
Current release17031.23, February 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoBSDcommercialOpen 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++C++Scala
Server operating systemsLinuxIllumos
Linux
OS X
Windows
LinuxLinux
OS X
Windows
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.yesnonono
Secondary indexesyesnonono
SQL infoSupport of SQLnonoA subset of ANSI SQL is implementedSQL-like DML and DDL statements
APIs and other access methodsLDAPRESTful HTTP APIJDBC
ODBC
Supported programming languagesAll languages with LDAP bindingsC++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C#
C++
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnononono
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionnoneFixed-grid hypercubesyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneReal-time block device replication (DRBD)none
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 configurationImmediate ConsistencyImmediate Consistency
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 persistentyesyes infowith automatic compression on writesyesyes
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 authenticationnoyesno

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Atos Standard Common RepositoryLevelDBSpaceTimeSpark SQL
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