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DBMS > Google Cloud Datastore vs. JanusGraph vs. Kinetica vs. RDF4J

System Properties Comparison Google Cloud Datastore vs. JanusGraph vs. Kinetica vs. RDF4J

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonKinetica  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017Fully vectorized database across both GPUs and CPUsRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelDocument storeGraph DBMSRelational DBMSRDF store
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score1.94
Rank#129  Overall
#12  Graph DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Websitecloud.google.com/­datastorejanusgraph.orgwww.kinetica.comrdf4j.org
Technical documentationcloud.google.com/­datastore/­docsdocs.janusgraph.orgdocs.kinetica.comrdf4j.org/­documentation
DeveloperGoogleLinux Foundation; originally developed as Titan by AureliusKineticaSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2008201720122004
Current release0.6.3, February 20237.1, August 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++Java
Server operating systemshostedLinux
OS X
Unix
Windows
LinuxLinux
OS X
Unix
Windows
Data schemeschema-freeyesyesyes infoRDF Schemas
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 indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query language (GQL)noSQL-like DML and DDL statementsno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
JDBC
ODBC
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Clojure
Java
Python
C++
Java
JavaScript (Node.js)
Python
Java
PHP
Python
Server-side scripts infoStored proceduresusing Google App Engineyesuser defined functionsyes
TriggersCallbacks using the Google Apps Engineyesyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)Shardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosyesSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyes infovia Faunus, a graph analytics enginenono
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 Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDnoACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyesyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)User authentification and security via Rexster Graph ServerAccess rights for users and roles on table levelno

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More resources
Google Cloud DatastoreJanusGraph infosuccessor of TitanKineticaRDF4J infoformerly known as Sesame
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