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

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

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonStardog  Xexclude from comparisonTimescaleDB  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 PlatformEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualizationA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLTime Series DBMS for IoT Applications
Primary database modelDocument storeGraph DBMS
RDF store
Time Series DBMSTime 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
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitecloud.google.com/­datastorewww.stardog.comwww.timescale.comyanza.com
Technical documentationcloud.google.com/­datastore/­docsdocs.stardog.comdocs.timescale.com
DeveloperGoogleStardog-UnionTimescaleYanza
Initial release2008201020172015
Current release7.3.0, May 20202.15.0, May 2024
License infoCommercial or Open Sourcecommercialcommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/studentsOpen Source infoApache 2.0commercial 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 languageJavaC
Server operating systemshostedLinux
macOS
Windows
Linux
OS X
Windows
Windows
Data schemeschema-freeschema-free and OWL/RDFS-schema supportyesschema-free
Typing infopredefined data types such as float or dateyes, details hereyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesno
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.nono infoImport/export of XML data possibleyesno
Secondary indexesyesyes infosupports real-time indexing in full-text and geospatialyesno
SQL infoSupport of SQLSQL-like query language (GQL)Yes, compatible with all major SQL variants through dedicated BI/SQL Serveryes infofull PostgreSQL SQL syntaxno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
any language that supports HTTP calls
Server-side scripts infoStored proceduresusing Google App Engineuser defined functions and aggregates, HTTP Server extensions in Javauser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellno
TriggersCallbacks using the Google Apps Engineyes infovia event handlersyesyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, across time and space (hash partitioning) attributesnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosMulti-source replication in HA-ClusterSource-replica replication with hot standby and reads on replicas infonone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonono
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 in HA-ClusterImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyes inforelationships in graphsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACIDno
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.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and rolesfine grained access rights according to SQL-standardno

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More resources
Google Cloud DatastoreStardogTimescaleDBYanza
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