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DBMS > Atos Standard Common Repository vs. Dragonfly vs. etcd vs. Google Cloud Bigtable vs. SiteWhere

System Properties Comparison Atos Standard Common Repository vs. Dragonfly vs. etcd vs. Google Cloud Bigtable vs. SiteWhere

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonDragonfly  Xexclude from comparisonetcd  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonSiteWhere  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 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 storeGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.M2M integration platform for persisting/querying time series data
Primary database modelDocument store
Key-value store
Key-value storeKey-value storeKey-value store
Wide column store
Time 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
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.06
Rank#356  Overall
#35  Time Series DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorygithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
etcd.io
github.com/­etcd-io/­etcd
cloud.google.com/­bigtablegithub.com/­sitewhere/­sitewhere
Technical documentationwww.dragonflydb.io/­docsetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
cloud.google.com/­bigtable/­docssitewhere1.sitewhere.io/­index.html
DeveloperAtos Convergence CreatorsDragonflyDB team and community contributorsGoogleSiteWhere
Initial release2016202320152010
Current release17031.0, March 20233.4, August 2019
License infoCommercial or Open SourcecommercialOpen Source infoBSL 1.1Open Source infoApache Version 2.0commercialOpen Source infoCommon Public Attribution License Version 1.0
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 languageJavaC++GoJava
Server operating systemsLinuxLinuxFreeBSD
Linux
Windows infoexperimental
hostedLinux
OS X
Windows
Data schemeSchema and schema-less with LDAP viewsscheme-freeschema-freeschema-freepredefined scheme
Typing infopredefined data types such as float or dateoptionalstrings, hashes, lists, sets, sorted sets, bit arraysnonoyes
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 SQLnonononono
APIs and other access methodsLDAPProprietary protocol infoRESP - REdis Serialization ProtocolgRPC
JSON over HTTP
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP REST
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#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoLuanono
Triggersyespublish/subscribe channels provide some trigger functionalityyes, watching key changesno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingSharding infobased on HBase
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.Internal replication in Colossus, and regional replication between two clusters in different zonesselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
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 scriptsnoAtomic single-row operationsno
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.yesyesnonono
User concepts infoAccess controlLDAP bind authenticationPassword-based authenticationnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users with fine-grained authorization concept

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More resources
Atos Standard Common RepositoryDragonflyetcdGoogle Cloud BigtableSiteWhere
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