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

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

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonInfinityDB  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 networksA Java embedded Key-Value Store which extends the Java Map interfaceSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Key-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.07
Rank#359  Overall
#54  Key-value stores
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositoryboilerbay.comspark.apache.org/­sql
Technical documentationboilerbay.com/­infinitydb/­manualspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAtos Convergence CreatorsBoiler Bay Inc.Apache Software Foundation
Initial release201620022014
Current release17034.03.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen 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 languageJavaJavaScala
Server operating systemsLinuxAll OS with a Java VMLinux
OS X
Windows
Data schemeSchema and schema-less with LDAP viewsyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeyes
Typing infopredefined data types such as float or dateoptionalyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyes
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 indexesyesno infomanual creation possible, using inversions based on multi-value capabilityno
SQL infoSupport of SQLnonoSQL-like DML and DDL statements
APIs and other access methodsLDAPAccess via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
JDBC
ODBC
Supported programming languagesAll languages with LDAP bindingsJavaJava
Python
R
Scala
Server-side scripts infoStored proceduresnonono
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency infoREAD-COMMITTED or SERIALIZED
Foreign keys infoReferential integritynono infomanual creation possible, using inversions based on multi-value capabilityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACID infoOptimistic locking for transactions; no isolation for bulk loadsno
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.yesnono
User concepts infoAccess controlLDAP bind authenticationnono

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Atos Standard Common RepositoryInfinityDBSpark SQL
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