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

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

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonDragonfly  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 networksA drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceA 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
Key-value storeKey-value storeRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.41
Rank#266  Overall
#38  Key-value stores
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-repositorygithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
etcd.io
github.com/­etcd-io/­etcd
hive.apache.orgwww.circonus.com/solutions/time-series-database/
Technical documentationwww.dragonflydb.io/­docsetcd.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 CreatorsDragonflyDB team and community contributorsApache Software Foundation infoinitially developed by FacebookCirconus LLC.
Initial release2016202320122017
Current release17031.0, March 20233.4, August 20193.1.3, April 2022V0.10.20, January 2018
License infoCommercial or Open SourcecommercialOpen Source infoBSL 1.1Open 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 languageJavaC++GoJavaC and C++
Server operating systemsLinuxLinuxFreeBSD
Linux
Windows infoexperimental
All OS with a Java VMLinux
Data schemeSchema and schema-less with LDAP viewsscheme-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateoptionalstrings, hashes, lists, sets, sorted sets, bit arraysnoyesyes 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.yesnonono
Secondary indexesyesnonoyesno
SQL infoSupport of SQLnononoSQL-like DML and DDL statementsSQL-like query language (Circonus Analytics Query Language: CAQL)
APIs and other access methodsLDAPProprietary protocol infoRESP - REdis Serialization ProtocolgRPC
JSON over HTTP
JDBC
ODBC
Thrift
HTTP API
Supported programming languagesAll languages with LDAP bindingsC
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
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 proceduresnoLuanoyes infouser defined functions and integration of map-reduceyes, in Lua
Triggersyespublish/subscribe channels provide some trigger functionalityyes, watching key changesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingAutomatic, metric affinity per node
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationUsing 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 configurationEventual ConsistencyImmediate ConsistencyEventual ConsistencyImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsAtomic execution of command blocks and scriptsnonono
Concurrency infoSupport for concurrent manipulation of datayesyes, strict serializability by the serveryesyesyes
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.yesyesnono
User concepts infoAccess controlLDAP bind authenticationPassword-based authenticationnoAccess rights for users, groups and rolesno

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More resources
Atos Standard Common RepositoryDragonflyetcdHiveIRONdb
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