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DBMS > Atos Standard Common Repository vs. Google Cloud Bigtable vs. Ingres vs. Riak KV

System Properties Comparison Atos Standard Common Repository vs. Google Cloud Bigtable vs. Ingres vs. Riak KV

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonIngres  Xexclude from comparisonRiak KV  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 networksGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Well established RDBMSDistributed, fault tolerant key-value store
Primary database modelDocument store
Key-value store
Key-value store
Wide column store
Relational DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexes
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score4.11
Rank#81  Overall
#44  Relational DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorycloud.google.com/­bigtablewww.actian.com/­databases/­ingres
Technical documentationcloud.google.com/­bigtable/­docsdocs.actian.com/­ingreswww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperAtos Convergence CreatorsGoogleActian CorporationOpenSource, formerly Basho Technologies
Initial release201620151974 infooriginally developed at University Berkely in early 1970s2009
Current release170311.2, May 20223.2.0, December 2022
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCErlang
Server operating systemsLinuxhostedAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Linux
OS X
Data schemeSchema and schema-less with LDAP viewsschema-freeyesschema-free
Typing infopredefined data types such as float or dateoptionalnoyesno
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 availableno
Secondary indexesyesnoyesrestricted
SQL infoSupport of SQLnonoyesno
APIs and other access methodsLDAPgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
HTTP API
Native Erlang Interface
Supported programming languagesAll languages with LDAP bindingsC#
C++
Go
Java
JavaScript (Node.js)
Python
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
Server-side scripts infoStored proceduresnonoyesErlang
Triggersyesnoyesyes infopre-commit hooks and post-commit hooks
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"
Replication methods infoMethods for redundantly storing data on multiple nodesyesInternal replication in Colossus, and regional replication between two clusters in different zonesIngres Replicatorselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesno infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsAtomic single-row operationsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCCyes
Durability infoSupport for making data persistentyesyesyesyes
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 authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardyes, using Riak Security

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More resources
Atos Standard Common RepositoryGoogle Cloud BigtableIngresRiak KV
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