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DBMS > Kinetica vs. NCache vs. Solr vs. SpatiaLite

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

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonNCache  Xexclude from comparisonSolr  Xexclude from comparisonSpatiaLite  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsOpen-Source and Enterprise in-memory Key-Value StoreA widely used distributed, scalable search engine based on Apache LuceneSpatial extension of SQLite
Primary database modelRelational DBMSKey-value storeSearch engineSpatial DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Search engine infoUsing distributed Lucene
Spatial DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.94
Rank#195  Overall
#29  Key-value stores
Score42.91
Rank#24  Overall
#3  Search engines
Score1.60
Rank#149  Overall
#3  Spatial DBMS
Websitewww.kinetica.comwww.alachisoft.com/­ncachesolr.apache.orgwww.gaia-gis.it/­fossil/­libspatialite/­index
Technical documentationdocs.kinetica.comwww.alachisoft.com/­resources/­docssolr.apache.org/­resources.htmlwww.gaia-gis.it/­gaia-sins/­spatialite_topics.html
DeveloperKineticaAlachisoftApache Software FoundationAlessandro Furieri
Initial release2012200520062008
Current release7.1, August 20215.3.3, April 20249.6.0, April 20245.0.0, August 2020
License infoCommercial or Open SourcecommercialOpen Source infoEnterprise Edition availableOpen 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#, .NET, .NET Core, JavaJavaC++
Server operating systemsLinuxLinux
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)server-less
Data schemeyesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyespartial infoSupported data types are Lists, Queues, Hashsets, Dictionary and Counteryes 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.nonoyesno
Secondary indexesyesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.Solr Parallel SQL Interfaceyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
IDistributedCache
JCache
LINQ
Proprietary native API
Java API
RESTful HTTP/JSON API
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresuser defined functionsno infosupport for stored procedures with SQL-Server CLRJava pluginsno
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infoNotificationsyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesShardingyesShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes, with selectable consistency levelyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesspark-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
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology
Eventual Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic locking and pessimistic lockingoptimistic 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 RAMyesyesyes
User concepts infoAccess controlAccess rights for users and roles on table levelAuthentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)yesno
More information provided by the system vendor
KineticaNCacheSolrSpatiaLite
Specific characteristicsNCache has been the market leader in .NET Distributed Caching since 2005 . NCache...
» more
Competitive advantagesNCache is 100% .NET/ .NET Core based which fully supports ASP.NET Core Sessions ,...
» more
Typical application scenariosNCache enables industries like retail, finance, banking IoT, travel, ecommerce, healthcare...
» more
Key customersBank of America, Citi, Natures Way, Charter Spectrum, Barclays, Henry Schein, GBM,...
» more
Market metricsMarket Leader in .NET Distributed Caching since 2005.
» more
Licensing and pricing modelsNCache Open Source is free on an as-is basis without any support. NCache Enterprise...
» more

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More resources
KineticaNCacheSolrSpatiaLite
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