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DBMS > Google Cloud Datastore vs. jBASE vs. Stardog vs. Vitess

System Properties Comparison Google Cloud Datastore vs. jBASE vs. Stardog vs. Vitess

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonjBASE  Xexclude from comparisonStardog  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA robust multi-value DBMS comprising development tools and middlewareEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualizationScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelDocument storeMultivalue DBMSGraph DBMS
RDF store
Relational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score1.41
Rank#159  Overall
#3  Multivalue DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitecloud.google.com/­datastorewww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-jbasewww.stardog.comvitess.io
Technical documentationcloud.google.com/­datastore/­docsdocs.rocketsoftware.com/­bundle?labelkey=jbase_5.9docs.stardog.comvitess.io/­docs
DeveloperGoogleRocket Software (formerly Zumasys)Stardog-UnionThe Linux Foundation, PlanetScale
Initial release2008199120102013
Current release5.77.3.0, May 202015.0.2, December 2022
License infoCommercial or Open Sourcecommercialcommercialcommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/studentsOpen Source infoApache Version 2.0, commercial licenses available
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 languageJavaGo
Server operating systemshostedAIX
Linux
Windows
Linux
macOS
Windows
Docker
Linux
macOS
Data schemeschema-freeschema-freeschema-free and OWL/RDFS-schema supportyes
Typing infopredefined data types such as float or dateyes, details hereoptionalyesyes
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 possible
Secondary indexesyesyes infosupports real-time indexing in full-text and geospatialyes
SQL infoSupport of SQLSQL-like query language (GQL)Embedded SQL for jBASE in BASICYes, compatible with all major SQL variants through dedicated BI/SQL Serveryes infowith proprietary extensions
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based 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
MySQL protocol
ODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Basic
Jabbascript
Java
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresusing Google App Engineyesuser defined functions and aggregates, HTTP Server extensions in Javayes infoproprietary syntax
TriggersCallbacks using the Google Apps Engineyesyes infovia event handlersyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosyesMulti-source replication in HA-ClusterMulti-source replication
Source-replica replication
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-ClusterEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyes inforelationships in graphsyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
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.noyesyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights can be defined down to the item levelAccess rights for users and rolesUsers with fine-grained authorization concept infono user groups or roles

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More resources
Google Cloud DatastorejBASEStardogVitess
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