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DBMS > Atos Standard Common Repository vs. BigchainDB vs. Percona Server for MongoDB vs. Spark SQL vs. Splice Machine

System Properties Comparison Atos Standard Common Repository vs. BigchainDB vs. Percona Server for MongoDB vs. Spark SQL vs. Splice Machine

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonBigchainDB  Xexclude from comparisonPercona Server for MongoDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSplice Machine  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 networksBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsA drop-in replacement for MongoDB Community Edition with enterprise-grade features.Spark SQL is a component on top of 'Spark Core' for structured data processingOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument store
Key-value store
Document storeDocument storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.79
Rank#212  Overall
#36  Document stores
Score0.52
Rank#254  Overall
#39  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.bigchaindb.comwww.percona.com/­mongodb/­software/­percona-server-for-mongodbspark.apache.org/­sqlsplicemachine.com
Technical documentationbigchaindb.readthedocs.io/­en/­latestdocs.percona.com/­percona-distribution-for-mongodbspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsplicemachine.com/­how-it-works
DeveloperAtos Convergence CreatorsPerconaApache Software FoundationSplice Machine
Initial release20162016201520142014
Current release17033.4.10-2.10, November 20173.5.0 ( 2.13), September 20233.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoAGPL v3Open Source infoGPL Version 2Open Source infoApache 2.0Open Source infoAGPL 3.0, commercial license available
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 languageJavaPythonC++ScalaJava
Server operating systemsLinuxLinuxLinuxLinux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeSchema and schema-less with LDAP viewsschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateoptionalnoyesyesyes
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 indexesyesyesnoyes
SQL infoSupport of SQLnononoSQL-like DML and DDL statementsyes
APIs and other access methodsLDAPCLI Client
RESTful HTTP API
proprietary protocol using JSONJDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages with LDAP bindingsGo
Haskell
Java
JavaScript
Python
Ruby
Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk
Java
Python
R
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoJavaScriptnoyes infoJava
Triggersyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingShardingyes, utilizing Spark CoreShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factorSource-replica replicationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes,with MongoDB ord RethinkDByesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infovia In-Memory Enginenoyes
User concepts infoAccess controlLDAP bind authenticationyesAccess rights for users and rolesnoAccess rights for users, groups and roles according to SQL-standard

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More resources
Atos Standard Common RepositoryBigchainDBPercona Server for MongoDBSpark SQLSplice Machine
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