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DBMS > Atos Standard Common Repository vs. Citus vs. etcd vs. Hive vs. IRONdb

System Properties Comparison Atos Standard Common Repository vs. Citus vs. etcd vs. Hive vs. IRONdb

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonCitus  Xexclude from comparisonetcd  Xexclude from comparisonHive  Xexclude from comparisonIRONdb  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 hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLA distributed reliable key-value storedata warehouse software for querying and managing large distributed datasets, built on HadoopA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity
Primary database modelDocument store
Key-value store
Relational DBMSKey-value storeRelational DBMSTime Series DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score7.25
Rank#54  Overall
#5  Key-value stores
Score61.17
Rank#18  Overall
#12  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.citusdata.cometcd.io
github.com/­etcd-io/­etcd
hive.apache.orgwww.circonus.com/solutions/time-series-database/
Technical documentationdocs.citusdata.cometcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
cwiki.apache.org/­confluence/­display/­Hive/­Homedocs.circonus.com/irondb/category/getting-started
DeveloperAtos Convergence CreatorsApache Software Foundation infoinitially developed by FacebookCirconus LLC.
Initial release2016201020122017
Current release17038.1, December 20183.4, August 20193.1.3, April 2022V0.10.20, January 2018
License infoCommercial or Open SourcecommercialOpen Source infoAGPL, commercial license also availableOpen Source infoApache Version 2.0Open Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaCGoJavaC and C++
Server operating systemsLinuxLinuxFreeBSD
Linux
Windows infoexperimental
All OS with a Java VMLinux
Data schemeSchema and schema-less with LDAP viewsyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateoptionalyesnoyesyes infotext, numeric, histograms
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.yesyes infospecific XML type available, but no XML query functionalitynono
Secondary indexesyesyesnoyesno
SQL infoSupport of SQLnoyes infostandard, with numerous extensionsnoSQL-like DML and DDL statementsSQL-like query language (Circonus Analytics Query Language: CAQL)
APIs and other access methodsLDAPADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC
JSON over HTTP
JDBC
ODBC
Thrift
HTTP API
Supported programming languagesAll languages with LDAP bindings.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
C++
Java
PHP
Python
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Server-side scripts infoStored proceduresnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.noyes infouser defined functions and integration of map-reduceyes, in Lua
Triggersyesyesyes, watching key changesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingShardingAutomatic, metric affinity per node
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replication infoother methods possible by using 3rd party extensionsUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.selectable replication factorconfigurable replication factor, datacenter aware
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDnonono
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.yesnonono
User concepts infoAccess controlLDAP bind authenticationfine grained access rights according to SQL-standardnoAccess rights for users, groups and rolesno

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More resources
Atos Standard Common RepositoryCitusetcdHiveIRONdb
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