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DBMS > Citus vs. FeatureBase vs. Solr vs. Typesense

System Properties Comparison Citus vs. FeatureBase vs. Solr vs. Typesense

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonFeatureBase  Xexclude from comparisonSolr  Xexclude from comparisonTypesense  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLReal-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.A widely used distributed, scalable search engine based on Apache LuceneA typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity
Primary database modelRelational DBMSRelational DBMSSearch engineSearch engine
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
Score0.22
Rank#309  Overall
#139  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score0.79
Rank#210  Overall
#14  Search engines
Websitewww.citusdata.comwww.featurebase.comsolr.apache.orgtypesense.org
Technical documentationdocs.citusdata.comdocs.featurebase.comsolr.apache.org/­resources.htmltypesense.org/­docs
DeveloperMolecula and Pilosa Open Source ContributorsApache Software Foundation
Initial release2010201720062015
Current release8.1, December 20182022, May 20229.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialOpen Source infoApache Version 2Open Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCGoJavaC++
Server operating systemsLinuxLinux
macOS
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
Data schemeyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsschema-free infopre-defined schema optional
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 functionalitynoyes
Secondary indexesyesnoyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsSQL queriesSolr Parallel SQL Interfaceno
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC
JDBC
Kafka Connector
ODBC
Java API
RESTful HTTP/JSON API
RESTful HTTP API
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
.Net infocommunity maintained
Clojure infocommunity maintained
Dart infocommunity maintained
Go infocommunity maintained
Java infocommunity maintained
JavaScript
Perl infocommunity maintained
PHP
Python
Ruby
Rust infocommunity maintained
Swift infocommunity maintained
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.Java pluginsno
Triggersyesnoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsyesyesMulti-source replication using RAFT
MapReduce infoOffers an API for user-defined Map/Reduce methodsnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesoptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, using Linux fsyncyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardyes

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