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DBMS > Citus vs. HarperDB vs. Solr vs. Spark SQL

System Properties Comparison Citus vs. HarperDB vs. Solr vs. Spark SQL

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonHarperDB  Xexclude from comparisonSolr  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLUltra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.A widely used distributed, scalable search engine based on Apache LuceneSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSDocument storeSearch engineRelational DBMS
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.15
Rank#117  Overall
#56  Relational DBMS
Score0.60
Rank#244  Overall
#38  Document stores
Score41.02
Rank#24  Overall
#3  Search engines
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.citusdata.comwww.harperdb.iosolr.apache.orgspark.apache.org/­sql
Technical documentationdocs.citusdata.comdocs.harperdb.io/­docssolr.apache.org/­resources.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperHarperDBApache Software FoundationApache Software Foundation
Initial release2010201720062014
Current release8.1, December 20183.1, August 20219.6.1, May 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercial infofree community edition availableOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCNode.jsJavaScala
Server operating systemsLinuxLinux
OS X
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Data schemeyesdynamic schemayes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyes infoJSON data typesyes 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
Secondary indexesyesyesyes infoAll search fields are automatically indexedno
SQL infoSupport of SQLyes infostandard, with numerous extensionsSQL-like data manipulation statementsSolr Parallel SQL InterfaceSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
Java API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.Custom Functions infosince release 3.1Java pluginsno
Triggersyesnoyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesShardingA table resides as a whole on one (or more) nodes in a clusterShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsyes infothe nodes on which a table resides can be definedyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of specific operationsoptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users and rolesyesno

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CitusHarperDBSolrSpark SQL
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