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DBMS > Google Cloud Datastore vs. LokiJS vs. Stardog vs. TypeDB

System Properties Comparison Google Cloud Datastore vs. LokiJS vs. Stardog vs. TypeDB

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonLokiJS  Xexclude from comparisonStardog  Xexclude from comparisonTypeDB infoformerly named Grakn  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformIn-memory JavaScript DBMSEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualizationTypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language
Primary database modelDocument storeDocument storeGraph DBMS
RDF store
Graph DBMS
Relational DBMS infoOften described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score0.49
Rank#260  Overall
#42  Document stores
Score2.07
Rank#122  Overall
#11  Graph DBMS
#6  RDF stores
Score0.70
Rank#230  Overall
#20  Graph DBMS
#106  Relational DBMS
Websitecloud.google.com/­datastoregithub.com/­techfort/­LokiJSwww.stardog.comtypedb.com
Technical documentationcloud.google.com/­datastore/­docstechfort.github.io/­LokiJSdocs.stardog.comtypedb.com/­docs
DeveloperGoogleStardog-UnionVaticle
Initial release2008201420102016
Current release7.3.0, May 20202.26.3, January 2024
License infoCommercial or Open SourcecommercialOpen Sourcecommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/studentsOpen Source infoGPL Version 3, commercial licenses available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScriptJavaJava
Server operating systemshostedserver-less, requires a JavaScript environment (browser, Node.js)Linux
macOS
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeschema-free and OWL/RDFS-schema supportyes
Typing infopredefined data types such as float or dateyes, details herenoyesyes
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 infoImport/export of XML data possibleno
Secondary indexesyesyes infovia viewsyes infosupports real-time indexing in full-text and geospatialyes
SQL infoSupport of SQLSQL-like query language (GQL)noYes, compatible with all major SQL variants through dedicated BI/SQL Serverno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JavaScript APIGraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaScript.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresusing Google App EngineView functions in JavaScriptuser defined functions and aggregates, HTTP Server extensions in Javano
TriggersCallbacks using the Google Apps Engineyesyes infovia event handlersno
Partitioning methods infoMethods for storing different data on different nodesShardingnonenoneSharding infoby using Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosnoneMulti-source replication in HA-ClusterMulti-source replication infoby using Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyesnoyes infoby using Apache Kafka and Apache Zookeeper
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.noneImmediate Consistency in HA-ClusterImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyes inforelationships in graphsno infosubstituted by the relationship feature
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno infoatomic operations within a single collection possibleACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infoSerialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noAccess rights for users and rolesyes infoat REST API level; other APIs in progress
More information provided by the system vendor
Google Cloud DatastoreLokiJSStardogTypeDB infoformerly named Grakn
Specific characteristicsTypeDB is a polymorphic database with a conceptual data model, a strong subtyping...
» more
Competitive advantagesTypeDB provides a new level of expressivity, extensibility, interoperability, and...
» more
Typical application scenariosLife sciences : TypeDB makes working with biological data much easier and accelerates...
» more
Licensing and pricing modelsApache f or language drivers, and AGPL and Commercial for the database server. The...
» more

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More resources
Google Cloud DatastoreLokiJSStardogTypeDB infoformerly named Grakn
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