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DBMS > Atos Standard Common Repository vs. Blueflood vs. IRONdb vs. Microsoft Azure Table Storage vs. Spark SQL

System Properties Comparison Atos Standard Common Repository vs. Blueflood vs. IRONdb vs. Microsoft Azure Table Storage vs. Spark SQL

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonBlueflood  Xexclude from comparisonIRONdb  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSpark SQL  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksScalable TimeSeries DBMS based on CassandraA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityA Wide Column Store for rapid development using massive semi-structured datasetsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Time Series DBMSTime Series DBMSWide column storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.06
Rank#353  Overall
#34  Time Series DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositoryblueflood.iowww.circonus.com/solutions/time-series-database/azure.microsoft.com/­en-us/­services/­storage/­tablesspark.apache.org/­sql
Technical documentationgithub.com/­rax-maas/­blueflood/­wikidocs.circonus.com/irondb/category/getting-startedspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAtos Convergence CreatorsRackspaceCirconus LLC.MicrosoftApache Software Foundation
Initial release20162013201720122014
Current release1703V0.10.20, January 20183.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC and C++Scala
Server operating systemsLinuxLinux
OS X
LinuxhostedLinux
OS X
Windows
Data schemeSchema and schema-less with LDAP viewspredefined schemeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateoptionalyesyes infotext, numeric, histogramsyesyes
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.yesnononono
Secondary indexesyesnononono
SQL infoSupport of SQLnonoSQL-like query language (Circonus Analytics Query Language: CAQL)noSQL-like DML and DDL statements
APIs and other access methodsLDAPHTTP RESTHTTP APIRESTful HTTP APIJDBC
ODBC
Supported programming languagesAll languages with LDAP bindings.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonoyes, in Luanono
Triggersyesnononono
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionSharding infobased on CassandraAutomatic, metric affinity per nodeSharding infoImplicit feature of the cloud serviceyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factor infobased on Cassandraconfigurable replication factor, datacenter awareyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate consistency per node, eventual consistency across nodesImmediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsnonooptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnononono
User concepts infoAccess controlLDAP bind authenticationnonoAccess rights based on private key authentication or shared access signaturesno

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More resources
Atos Standard Common RepositoryBluefloodIRONdbMicrosoft Azure Table StorageSpark SQL
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