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DBMS > Google Cloud Datastore vs. openGemini vs. Riak KV vs. Trafodion

System Properties Comparison Google Cloud Datastore vs. openGemini vs. Riak KV vs. Trafodion

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonopenGemini  Xexclude from comparisonRiak KV  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformAn open source distributed Time Series DBMS with high concurrency, high performance, and high scalabilityDistributed, fault tolerant key-value storeTransactional SQL-on-Hadoop DBMS
Primary database modelDocument storeTime Series 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
Score4.36
Rank#72  Overall
#12  Document stores
Score0.09
Rank#361  Overall
#37  Time Series DBMS
Score4.01
Rank#79  Overall
#9  Key-value stores
Websitecloud.google.com/­datastorewww.opengemini.org
github.com/­openGemini
trafodion.apache.org
Technical documentationcloud.google.com/­datastore/­docsdocs.opengemini.org/­guidewww.tiot.jp/­riak-docs/­riak/­kv/­latesttrafodion.apache.org/­documentation.html
DeveloperGoogleHuawei and openGemini communityOpenSource, formerly Basho TechnologiesApache Software Foundation, originally developed by HP
Initial release2008202220092014
Current release1.1, July 20233.2.0, December 20222.3.0, February 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache version 2, commercial enterprise editionOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoErlangC++, Java
Server operating systemshostedLinux
Windows
Linux
OS X
Linux
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyes, details hereInteger, Float, Boolean, Stringnoyes
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.nononono
Secondary indexesyesyesrestrictedyes
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like query languagenoyes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP RESTHTTP API
Native Erlang Interface
ADO.NET
JDBC
ODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
Python
Rust
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
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresusing Google App EnginenoErlangJava Stored Procedures
TriggersCallbacks using the Google Apps Enginenoyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infono "single point of failure"Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyesselectable replication factoryes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownoyesyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnono infolinks between data sets can be storedyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnonoACID
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.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Administrators and common users accountsyes, using Riak Securityfine grained access rights according to SQL-standard

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More resources
Google Cloud DatastoreopenGeminiRiak KVTrafodion
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