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

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

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonInfinityDB  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 PlatformA Java embedded Key-Value Store which extends the Java Map interfaceDistributed, fault tolerant key-value storeTransactional SQL-on-Hadoop DBMS
Primary database modelDocument storeKey-value storeKey-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
Score0.08
Rank#365  Overall
#55  Key-value stores
Score4.01
Rank#79  Overall
#9  Key-value stores
Websitecloud.google.com/­datastoreboilerbay.comtrafodion.apache.org
Technical documentationcloud.google.com/­datastore/­docsboilerbay.com/­infinitydb/­manualwww.tiot.jp/­riak-docs/­riak/­kv/­latesttrafodion.apache.org/­documentation.html
DeveloperGoogleBoiler Bay Inc.OpenSource, formerly Basho TechnologiesApache Software Foundation, originally developed by HP
Initial release2008200220092014
Current release4.03.2.0, December 20222.3.0, February 2019
License infoCommercial or Open SourcecommercialcommercialOpen 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

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Implementation languageJavaErlangC++, Java
Server operating systemshostedAll OS with a Java VMLinux
OS X
Linux
Data schemeschema-freeyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeschema-freeyes
Typing infopredefined data types such as float or dateyes, details hereyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysnoyes
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 indexesyesno infomanual creation possible, using inversions based on multi-value capabilityrestrictedyes
SQL infoSupport of SQLSQL-like query language (GQL)nonoyes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
HTTP API
Native Erlang Interface
ADO.NET
JDBC
ODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaC 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 nodesShardingnoneSharding infono "single point of failure"Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosnoneselectable 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.Immediate Consistency infoREAD-COMMITTED or SERIALIZEDEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsno infomanual creation possible, using inversions based on multi-value capabilityno 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 TransactionsACID infoOptimistic locking for transactions; no isolation for bulk loadsnoACID
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.nonono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noyes, using Riak Securityfine grained access rights according to SQL-standard

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More resources
Google Cloud DatastoreInfinityDBRiak KVTrafodion
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