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DBMS > Atos Standard Common Repository vs. etcd vs. Oracle Berkeley DB vs. Sadas Engine vs. Spark SQL

System Properties Comparison Atos Standard Common Repository vs. etcd vs. Oracle Berkeley DB vs. Sadas Engine vs. Spark SQL

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonetcd  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSadas Engine  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 storeWidely used in-process key-value storeSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Key-value storeKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.03
Rank#54  Overall
#5  Key-value stores
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Score0.07
Rank#373  Overall
#157  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositoryetcd.io
github.com/­etcd-io/­etcd
www.oracle.com/­database/­technologies/­related/­berkeleydb.htmlwww.sadasengine.comspark.apache.org/­sql
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.oracle.com/­cd/­E17076_05/­html/­index.htmlwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAtos Convergence CreatorsOracle infooriginally developed by Sleepycat, which was acquired by OracleSADAS s.r.l.Apache Software Foundation
Initial release2016199420062014
Current release17033.4, August 201918.1.40, May 20208.03.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infocommercial license availablecommercial infofree trial version availableOpen Source infoApache 2.0
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 languageJavaGoC, Java, C++ (depending on the Berkeley DB edition)C++Scala
Server operating systemsLinuxFreeBSD
Linux
Windows infoexperimental
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
AIX
Linux
Windows
Linux
OS X
Windows
Data schemeSchema and schema-less with LDAP viewsschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateoptionalnonoyesyes
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.yesnoyes infoonly with the Berkeley DB XML editionnono
Secondary indexesyesnoyesyesno
SQL infoSupport of SQLnonoyes infoSQL interfaced based on SQLite is availableyesSQL-like DML and DDL statements
APIs and other access methodsLDAPgRPC
JSON over HTTP
JDBC
ODBC
Proprietary protocol
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
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
.Net
C
C#
C++
Groovy
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnonononono
Triggersyesyes, watching key changesyes infoonly for the SQL APInono
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionnonehorizontal partitioningyes, 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.Source-replica replicationnonenone
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 configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesnoyesyes infomanaged by 'Learn by Usage'no
User concepts infoAccess controlLDAP bind authenticationnonoAccess rights for users, groups and roles according to SQL-standardno

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More resources
Atos Standard Common RepositoryetcdOracle Berkeley DBSadas EngineSpark SQL
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