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

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

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  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 networksEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Distributed, fault tolerant key-value store
Primary database modelDocument store
Key-value store
Relational DBMSKey-value store
Wide column store
Key-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
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score4.10
Rank#82  Overall
#9  Key-value stores
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.esgyn.cncloud.google.com/­bigtable
Technical documentationcloud.google.com/­bigtable/­docswww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperAtos Convergence CreatorsEsgynGoogleOpenSource, formerly Basho Technologies
Initial release2016201520152009
Current release17033.2.0, December 2022
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++, JavaErlang
Server operating systemsLinuxLinuxhostedLinux
OS X
Data schemeSchema and schema-less with LDAP viewsyesschema-freeschema-free
Typing infopredefined data types such as float or dateoptionalyesnono
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 indexesyesyesnorestricted
SQL infoSupport of SQLnoyesnono
APIs and other access methodsLDAPADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP API
Native Erlang Interface
Supported programming languagesAll languages with LDAP bindingsAll languages supporting JDBC/ODBC/ADO.NetC#
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 proceduresnoJava Stored ProceduresnoErlang
Triggersyesnonoyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingShardingSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Foreign keys infoReferential integritynoyesnono infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDAtomic single-row operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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 authenticationfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes, using Riak Security

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More resources
Atos Standard Common RepositoryEsgynDBGoogle Cloud BigtableRiak KV
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