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DBMS > Google Cloud Datastore vs. Kdb vs. Stardog vs. Yanza

System Properties Comparison Google Cloud Datastore vs. Kdb vs. Stardog vs. Yanza

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonKdb  Xexclude from comparisonStardog  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformHigh performance Time Series DBMSEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualizationTime Series DBMS for IoT Applications
Primary database modelDocument storeTime Series DBMS
Vector DBMS
Graph DBMS
RDF store
Time Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websitecloud.google.com/­datastorekx.comwww.stardog.comyanza.com
Technical documentationcloud.google.com/­datastore/­docscode.kx.comdocs.stardog.com
DeveloperGoogleKx Systems, a division of First Derivatives plcStardog-UnionYanza
Initial release20082000 infokdb was released 2000, kdb+ in 200320102015
Current release3.6, May 20187.3.0, May 2020
License infoCommercial or Open Sourcecommercialcommercial infofree 32-bit versioncommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/studentscommercial infofree version available
Cloud-based only infoOnly available as a cloud serviceyesnonono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageqJava
Server operating systemshostedLinux
OS X
Solaris
Windows
Linux
macOS
Windows
Windows
Data schemeschema-freeyesschema-free and OWL/RDFS-schema supportschema-free
Typing infopredefined data types such as float or dateyes, details hereyesyesno
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.noyesno infoImport/export of XML data possibleno
Secondary indexesyesyes infotable attribute 'grouped'yes infosupports real-time indexing in full-text and geospatialno
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like query language (q)Yes, compatible with all major SQL variants through dedicated BI/SQL Serverno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
HTTP API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
any language that supports HTTP calls
Server-side scripts infoStored proceduresusing Google App Engineuser defined functionsuser defined functions and aggregates, HTTP Server extensions in Javano
TriggersCallbacks using the Google Apps Engineyes infowith viewsyes infovia event handlersyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSource-replica replicationMulti-source replication in HA-Clusternone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowno infosimilar paradigm used for internal processingnono
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 ConsistencyImmediate Consistency in HA-ClusterImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesyes inforelationships in graphsno
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 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.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)rights management via user accountsAccess rights for users and rolesno
More information provided by the system vendor
Google Cloud DatastoreKdbStardogYanza
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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More resources
Google Cloud DatastoreKdbStardogYanza
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