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DBMS > Google Cloud Datastore vs. Kinetica vs. RDFox vs. Spark SQL

System Properties Comparison Google Cloud Datastore vs. Kinetica vs. RDFox vs. Spark SQL

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonRDFox  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformFully vectorized database across both GPUs and CPUsHigh performance knowledge graph and semantic reasoning engineSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeRelational DBMSGraph DBMS
RDF store
Relational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Relational DBMS
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
Score0.23
Rank#308  Overall
#25  Graph DBMS
#14  RDF stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitecloud.google.com/­datastorewww.kinetica.comwww.oxfordsemantic.techspark.apache.org/­sql
Technical documentationcloud.google.com/­datastore/­docsdocs.kinetica.comdocs.oxfordsemantic.techspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGoogleKineticaOxford Semantic TechnologiesApache Software Foundation
Initial release2008201220172014
Current release7.1, August 20216.0, Septermber 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen 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 languageC, C++C++Scala
Server operating systemshostedLinuxLinux
macOS
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyes infoRDF schemasyes
Typing infopredefined data types such as float or dateyes, details hereyesyesyes
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.nonono
Secondary indexesyesyesno
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like DML and DDL statementsnoSQL-like DML and DDL statements
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
RESTful HTTP API
SPARQL 1.1
JDBC
ODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
C
Java
Java
Python
R
Scala
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 rangeno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSource-replica replicationreplication via a shared file systemnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowno
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 Consistency in stand-alone mode, Eventual Consistency in replicated setups
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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 RAMyesno
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 levelRoles, resources, and access typesno

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More resources
Google Cloud DatastoreKineticaRDFoxSpark SQL
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