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DBMS > Atos Standard Common Repository vs. etcd vs. NSDb vs. Spark SQL

System Properties Comparison Atos Standard Common Repository vs. etcd vs. NSDb vs. Spark SQL

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonetcd  Xexclude from comparisonNSDb  Xexclude from comparisonSpark SQL  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 distributed reliable key-value storeScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Key-value storeTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.03
Rank#54  Overall
#5  Key-value stores
Score0.08
Rank#369  Overall
#40  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositoryetcd.io
github.com/­etcd-io/­etcd
nsdb.iospark.apache.org/­sql
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
nsdb.io/­Architecturespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAtos Convergence CreatorsApache Software Foundation
Initial release201620172014
Current release17033.4, August 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoJava, ScalaScala
Server operating systemsLinuxFreeBSD
Linux
Windows infoexperimental
Linux
macOS
Linux
OS X
Windows
Data schemeSchema and schema-less with LDAP viewsschema-freeyes
Typing infopredefined data types such as float or dateoptionalnoyes: int, bigint, decimal, stringyes
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 indexesyesnoall fields are automatically indexedno
SQL infoSupport of SQLnonoSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsLDAPgRPC
JSON over HTTP
gRPC
HTTP REST
WebSocket
JDBC
ODBC
Supported programming languagesAll languages with LDAP bindings.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
Java
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresnononono
Triggersyesyes, watching key changesno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesUsing Apache Luceneyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlLDAP bind authenticationnono

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More resources
Atos Standard Common RepositoryetcdNSDbSpark SQL
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