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DBMS > Google Cloud Datastore vs. Kinetica vs. RethinkDB vs. Rockset

System Properties Comparison Google Cloud Datastore vs. Kinetica vs. RethinkDB vs. Rockset

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonRethinkDB  Xexclude from comparisonRockset  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformFully vectorized database across both GPUs and CPUsDBMS for the Web with a mechanism to push updated query results to applications in realtime.A scalable, reliable search and analytics service in the cloud, built on RocksDB
Primary database modelDocument storeRelational DBMSDocument storeDocument store
Secondary database modelsSpatial DBMS
Time Series DBMS
Spatial DBMSRelational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score2.74
Rank#105  Overall
#19  Document stores
Score0.79
Rank#211  Overall
#35  Document stores
Websitecloud.google.com/­datastorewww.kinetica.comrethinkdb.comrockset.com
Technical documentationcloud.google.com/­datastore/­docsdocs.kinetica.comrethinkdb.com/­docsdocs.rockset.com
DeveloperGoogleKineticaThe Linux Foundation infosince July 2017Rockset
Initial release2008201220092019
Current release7.1, August 20212.4.1, August 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++C++C++
Server operating systemshostedLinuxLinux
OS X
Windows
hosted
Data schemeschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyes, details hereyesyes infostring, binary, float, bool, date, geometrydynamic typing
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 infoingestion from XML files supported
Secondary indexesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like DML and DDL statementsnoRead-only SQL queries, including JOINs
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
HTTP REST
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
C infocommunity-supported driver
C# infocommunity-supported driver
C++ infocommunity-supported driver
Clojure infocommunity-supported driver
Dart infocommunity-supported driver
Erlang infocommunity-supported driver
Go infocommunity-supported driver
Haskell infocommunity-supported driver
Java infoofficial driver
JavaScript (Node.js) infoofficial driver
Lisp infocommunity-supported driver
Lua infocommunity-supported driver
Objective-C infocommunity-supported driver
Perl infocommunity-supported driver
PHP infocommunity-supported driver
Python infoofficial driver
Ruby infoofficial driver
Scala infocommunity-supported driver
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresusing Google App Engineuser defined functionsno
TriggersCallbacks using the Google Apps Engineyes infotriggers when inserted values for one or more columns fall within a specified rangeClient-side triggers through changefeedsno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding inforange basedAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSource-replica replicationSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownoyesno
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 or Eventual Consistency depending on configurationImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoAtomic single-document operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCC basedyes
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.noyes infoGPU vRAM or System RAMno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table levelyes infousers and table-level permissionsAccess rights for users and organizations can be defined via Rockset console

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More resources
Google Cloud DatastoreKineticaRethinkDBRockset
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