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DBMS > Google Cloud Datastore vs. GraphDB vs. TigerGraph

System Properties Comparison Google Cloud Datastore vs. GraphDB vs. TigerGraph

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonGraphDB infoformer name: OWLIM  Xexclude from comparisonTigerGraph  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformEnterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL.A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelDocument storeGraph DBMS
RDF store
Graph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.43
Rank#78  Overall
#12  Document stores
Score2.60
Rank#129  Overall
#7  Graph DBMS
#4  RDF stores
Score2.21
Rank#145  Overall
#12  Graph DBMS
Websitecloud.google.com/­datastorewww.ontotext.comwww.tigergraph.com
Technical documentationcloud.google.com/­datastore/­docsgraphdb.ontotext.com/­documentationdocs.tigergraph.com
Social network pagesLinkedInTwitterGitHubYouTubeMedium
DeveloperGoogleOntotext
Initial release200820002017
Current release10.2, February 2023
License infoCommercial or Open Sourcecommercialcommercial infoSome plugins of GraphDB Workbench are open sourcedcommercial
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemshostedAll OS with a Java VM
Linux
OS X
Windows
Linux
Data schemeschema-freeschema-free and OWL/RDFS-schema support; RDF shapesyes
Typing infopredefined data types such as float or dateyes, details hereyesyes
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 indexesyesyes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes
SQL infoSupport of SQLSQL-like query language (GQL)stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBCSQL-like query language (GSQL)
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
C++
Java
Server-side scripts infoStored proceduresusing Google App Enginewell-defined plugin interfaces; JavaScript server-side extensibilityyes
TriggersCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownoyes
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, Eventual consistency (configurable in cluster mode per master or individual client request)
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyes infoConstraint checkingyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Default Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on.Role-based access control
More information provided by the system vendor
Google Cloud DatastoreGraphDB infoformer name: OWLIMTigerGraph
Specific characteristicsOntotext GraphDB is a semantic database engine that allows organizations to build...
» more
Competitive advantagesGraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
» more
Typical application scenariosMetadata enrichment and management, linked data publishing, semantic inferencing...
» more
Key customers​ GraphDB provides a platform for building next-generation AI and Knowledge Graph...
» more
Market metricsGraphDB is the most utilized semantic triplestore for mission-critical enterprise...
» more
Licensing and pricing modelsGraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition...
» more
News

Next-Gen Graph Technology: A CDO Matters Podcast with Ontotext’s CMO Doug Kimball
8 September 2023

Generative AI – How to Care For, and Properly Feed, Chatty Robots
1 September 2023

The Importance of the Semantic Knowledge Graph
1 September 2023

Data Integration Patterns in Knowledge Graph Building with GraphDB
25 August 2023

Why Establishing Data Context is the Key to Creating Competitive Advantage
22 August 2023

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Google Cloud DatastoreGraphDB infoformer name: OWLIMTigerGraph
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