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DBMS > Atos Standard Common Repository vs. Blueflood vs. IRONdb vs. PlanetScale vs. Spark SQL

System Properties Comparison Atos Standard Common Repository vs. Blueflood vs. IRONdb vs. PlanetScale vs. Spark SQL

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonBlueflood  Xexclude from comparisonIRONdb  Xexclude from comparisonPlanetScale  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 simplicityScalable, distributed, serverless MySQL database platform built on top of VitessSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Time Series DBMSTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.06
Rank#353  Overall
#34  Time Series DBMS
Score1.59
Rank#151  Overall
#70  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositoryblueflood.iowww.circonus.com/solutions/time-series-database/planetscale.comspark.apache.org/­sql
Technical documentationgithub.com/­rax-maas/­blueflood/­wikidocs.circonus.com/irondb/category/getting-startedplanetscale.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAtos Convergence CreatorsRackspaceCirconus LLC.PlanetScaleApache Software Foundation
Initial release20162013201720202014
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++GoScala
Server operating systemsLinuxLinux
OS X
LinuxDocker
Linux
macOS
Linux
OS X
Windows
Data schemeSchema and schema-less with LDAP viewspredefined schemeschema-freeyesyes
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.yesnonono
Secondary indexesyesnonoyesno
SQL infoSupport of SQLnonoSQL-like query language (Circonus Analytics Query Language: CAQL)yes infowith proprietary extensionsSQL-like DML and DDL statements
APIs and other access methodsLDAPHTTP RESTHTTP APIADO.NET
JDBC
MySQL protocol
ODBC
JDBC
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
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonoyes, in Luayes infoproprietary syntaxno
Triggersyesnonoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionSharding infobased on CassandraAutomatic, metric affinity per nodeShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factor infobased on Cassandraconfigurable replication factor, datacenter awareMulti-source replication
Source-replica replication
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 nodesEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynononoyes infonot for MyISAM storage engineno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsnonoACID at shard levelno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engineyes
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.yesnonoyesno
User concepts infoAccess controlLDAP bind authenticationnonoUsers with fine-grained authorization concept infono user groups or rolesno

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More resources
Atos Standard Common RepositoryBluefloodIRONdbPlanetScaleSpark SQL
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