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DBMS > Badger vs. Google Cloud Firestore vs. GraphDB vs. HugeGraph

System Properties Comparison Badger vs. Google Cloud Firestore vs. GraphDB vs. HugeGraph

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonGraphDB infoformer name: OWLIM  Xexclude from comparisonHugeGraph  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.Enterprise-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 fast-speed and highly-scalable Graph DBMS
Primary database modelKey-value storeDocument storeGraph DBMS
RDF store
Graph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score7.85
Rank#51  Overall
#8  Document stores
Score3.32
Rank#91  Overall
#6  Graph DBMS
#4  RDF stores
Score0.13
Rank#336  Overall
#32  Graph DBMS
Websitegithub.com/­dgraph-io/­badgerfirebase.google.com/­products/­firestorewww.ontotext.comgithub.com/­hugegraph
hugegraph.apache.org
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerfirebase.google.com/­docs/­firestoregraphdb.ontotext.com/­documentationhugegraph.apache.org/­docs
Social network pagesLinkedInTwitterYouTubeGitHubMedium
DeveloperDGraph LabsGoogleOntotextBaidu
Initial release2017201720002018
Current release10.4, October 20230.9
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercial infoSome plugins of GraphDB Workbench are open sourcedOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoJavaJava
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedAll OS with a Java VM
Linux
OS X
Windows
Linux
macOS
Unix
Data schemeschema-freeschema-freeschema-free and OWL/RDFS-schema support; RDF shapesyes
Typing infopredefined data types such as float or datenoyesyesyes
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.nononono
Secondary indexesnoyesyes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexesyes infoalso supports composite index and range index
SQL infoSupport of SQLnonostored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBCno
APIs and other access methodsAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1
Java API
RESTful HTTP API
TinkerPop Gremlin
Supported programming languagesGoGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Groovy
Java
Python
Server-side scripts infoStored proceduresnoyes, Firebase Rules & Cloud Functionswell-defined plugin interfaces; JavaScript server-side extensibilityasynchronous Gremlin script jobs
Triggersnoyes, with Cloud Functionsnono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnoneyes infodepending on used storage backend, e.g. Cassandra and HBase
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replicationMulti-source replicationyes infodepending on used storage backend, e.g. Cassandra and HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoUsing Cloud Dataflownovia hugegraph-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)Eventual Consistency
Foreign keys infoReferential integritynonoyes infoConstraint checkingyes infoedges in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACIDACID
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.noyes
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.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.Users, roles and permissions
More information provided by the system vendor
BadgerGoogle Cloud FirestoreGraphDB infoformer name: OWLIMHugeGraph
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
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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
BadgerGoogle Cloud FirestoreGraphDB infoformer name: OWLIMHugeGraph
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