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DBMS > Kinetica vs. Solr vs. Spark SQL

System Properties Comparison Kinetica vs. Solr vs. Spark SQL

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonSolr  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsA 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 DBMSSearch engineRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.kinetica.comsolr.apache.orgspark.apache.org/­sql
Technical documentationdocs.kinetica.comsolr.apache.org/­resources.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperKineticaApache Software FoundationApache Software Foundation
Initial release201220062014
Current release7.1, August 20219.5.0, February 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++JavaScala
Server operating systemsLinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Data schemeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyes 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.noyesno
Secondary indexesyesyes infoAll search fields are automatically indexedno
SQL infoSupport of SQLSQL-like DML and DDL statementsSolr Parallel SQL InterfaceSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
.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 functionsJava pluginsno
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMyesno
User concepts infoAccess controlAccess rights for users and roles on table levelyesno

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More resources
KineticaSolrSpark SQL
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