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DBMS > Atos Standard Common Repository vs. BigchainDB vs. Ingres vs. Riak KV vs. Spark SQL

System Properties Comparison Atos Standard Common Repository vs. BigchainDB vs. Ingres vs. Riak KV vs. Spark SQL

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonBigchainDB  Xexclude from comparisonIngres  Xexclude from comparisonRiak KV  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 networksBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsWell established RDBMSDistributed, fault tolerant key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Document storeRelational DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexesRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.79
Rank#212  Overall
#36  Document stores
Score4.11
Rank#81  Overall
#44  Relational DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.bigchaindb.comwww.actian.com/­databases/­ingresspark.apache.org/­sql
Technical documentationbigchaindb.readthedocs.io/­en/­latestdocs.actian.com/­ingreswww.tiot.jp/­riak-docs/­riak/­kv/­latestspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAtos Convergence CreatorsActian CorporationOpenSource, formerly Basho TechnologiesApache Software Foundation
Initial release201620161974 infooriginally developed at University Berkely in early 1970s20092014
Current release170311.2, May 20223.2.0, December 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoAGPL v3commercialOpen Source infoApache version 2, commercial enterprise editionOpen 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 languageJavaPythonCErlangScala
Server operating systemsLinuxLinuxAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Linux
OS X
Linux
OS X
Windows
Data schemeSchema and schema-less with LDAP viewsschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateoptionalnoyesnoyes
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.yesnono infobut tools for importing/exporting data from/to XML-files availablenono
Secondary indexesyesyesrestrictedno
SQL infoSupport of SQLnonoyesnoSQL-like DML and DDL statements
APIs and other access methodsLDAPCLI Client
RESTful HTTP API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
HTTP API
Native Erlang Interface
JDBC
ODBC
Supported programming languagesAll languages with LDAP bindingsGo
Haskell
Java
JavaScript
Python
Ruby
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyesErlangno
Triggersyesyesyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding infono "single point of failure"yes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factorIngres Replicatorselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesno infolinks between data sets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCCyesyes
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.yesnono
User concepts infoAccess controlLDAP bind authenticationyesfine grained access rights according to SQL-standardyes, using Riak Securityno

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More resources
Atos Standard Common RepositoryBigchainDBIngresRiak KVSpark SQL
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