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DBMS > Drizzle vs. Kinetica vs. Solr vs. SpatiaLite

System Properties Comparison Drizzle vs. Kinetica vs. Solr vs. SpatiaLite

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonKinetica  Xexclude from comparisonSolr  Xexclude from comparisonSpatiaLite  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Fully vectorized database across both GPUs and CPUsA widely used distributed, scalable search engine based on Apache LuceneSpatial extension of SQLite
Primary database modelRelational DBMSRelational DBMSSearch engineSpatial DBMS
Secondary database modelsSpatial DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.74
Rank#202  Overall
#97  Relational DBMS
Score58.53
Rank#19  Overall
#3  Search engines
Score1.94
Rank#122  Overall
#2  Spatial DBMS
Websitewww.kinetica.comlucene.apache.org/­solrwww.gaia-gis.it/­fossil/­libspatialite/­index
Technical documentationwww.kinetica.com/­docslucene.apache.org/­solr/­resources.htmlwww.gaia-gis.it/­gaia-sins/­spatialite_topics.html
DeveloperDrizzle project, originally started by Brian AkerKineticaApache Software FoundationAlessandro Furieri
Initial release2008201220062008
Current release7.2.4, September 20127.1, August 20218.11.1, December 20215.0.0, August 2020
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialOpen Source infoApache Version 2Open Source infoMPL 1.1, GPL v2.0 or LGPL v2.1
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 languageC++C, C++JavaC++
Server operating systemsFreeBSD
Linux
OS X
LinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)server-less
Data schemeyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
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.noyesno
Secondary indexesyesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLyes infowith proprietary extensionsSQL-like DML and DDL statementsSolr Parallel SQL Interfaceyes
APIs and other access methodsJDBCJDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
Supported programming languagesC
C++
Java
PHP
C++
Java
JavaScript (Node.js)
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnouser defined functionsJava pluginsno
Triggersno infohooks for callbacks inside the server can be used.yes infotriggers when inserted values for one or more columns fall within a specified rangeyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Foreign keys infoReferential integrityyesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnooptimistic 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.yes infoGPU vRAM or System RAMyesyes
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users and roles on table levelyesno
More information provided by the system vendor
DrizzleKineticaSolrSpatiaLite
Specific characteristicsNative and fully vectorized database across both GPUs and CPUs, with memory first...
» more
Competitive advantagesBest in class geospatial and temporal analytics. Lockless architecture provides real-time...
» more
Typical application scenariosAny application requiring (1) real time insights, (2) time series analysis (3) geospatial...
» more
Key customersCitibank, US Air Force, Softbank, OVO, Telkomsel, USPS, 2 of the top 3 US Telcos,...
» more
Market metricsThe largest IoT deployment in the world, NORAD, runs on Kinetica.
» more
Licensing and pricing modelsAlways Free Tier in the Cloud, Pay-As-You-Go Consumption Based Pricing, and Portable...
» more

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DrizzleKineticaSolrSpatiaLite
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