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DBMS > Citus vs. Google Cloud Firestore vs. Solr vs. Stardog

System Properties Comparison Citus vs. Google Cloud Firestore vs. Solr vs. Stardog

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonSolr  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLCloud 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.A widely used distributed, scalable search engine based on Apache LuceneEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelRelational DBMSDocument storeSearch engineGraph DBMS
RDF store
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score7.85
Rank#51  Overall
#8  Document stores
Score42.91
Rank#24  Overall
#3  Search engines
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websitewww.citusdata.comfirebase.google.com/­products/­firestoresolr.apache.orgwww.stardog.com
Technical documentationdocs.citusdata.comfirebase.google.com/­docs/­firestoresolr.apache.org/­resources.htmldocs.stardog.com
DeveloperGoogleApache Software FoundationStardog-Union
Initial release2010201720062010
Current release8.1, December 20189.6.0, April 20247.3.0, May 2020
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialOpen Source infoApache Version 2commercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJavaJava
Server operating systemsLinuxhostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
macOS
Windows
Data schemeyesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typingyes
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.yes infospecific XML type available, but no XML query functionalitynoyesno infoImport/export of XML data possible
Secondary indexesyesyesyes infoAll search fields are automatically indexedyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLyes infostandard, with numerous extensionsnoSolr Parallel SQL InterfaceYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Java 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
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes, Firebase Rules & Cloud FunctionsJava pluginsuser defined functions and aggregates, HTTP Server extensions in Java
Triggersyesyes, with Cloud Functionsyes infoUser configurable commands triggered on index changesyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsMulti-source replicationyesMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoUsing Cloud Dataflowspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integrityyesnonoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesoptimistic lockingACID
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.noyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.yesAccess rights for users and roles

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More resources
CitusGoogle Cloud FirestoreSolrStardog
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