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DBMS > Kinetica vs. Memcached vs. Microsoft Azure Table Storage vs. Solr

System Properties Comparison Kinetica vs. Memcached vs. Microsoft Azure Table Storage vs. Solr

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonMemcached  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsIn-memory key-value store, originally intended for cachingA Wide Column Store for rapid development using massive semi-structured datasetsA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSKey-value storeWide column storeSearch engine
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
Score19.42
Rank#32  Overall
#4  Key-value stores
Score4.48
Rank#75  Overall
#6  Wide column stores
Score42.91
Rank#24  Overall
#3  Search engines
Websitewww.kinetica.comwww.memcached.orgazure.microsoft.com/­en-us/­services/­storage/­tablessolr.apache.org
Technical documentationdocs.kinetica.comgithub.com/­memcached/­memcached/­wikisolr.apache.org/­resources.html
DeveloperKineticaDanga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalMicrosoftApache Software Foundation
Initial release2012200320122006
Current release7.1, August 20211.6.25, March 20249.6.0, April 2024
License infoCommercial or Open SourcecommercialOpen Source infoBSD licensecommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++CJava
Server operating systemsLinuxFreeBSD
Linux
OS X
Unix
Windows
hostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesschema-freeschema-freeyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesnoyesyes infosupports customizable data types and automatic typing
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.nonoyes
Secondary indexesyesnonoyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoSolr Parallel SQL Interface
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Proprietary protocolRESTful HTTP APIJava API
RESTful HTTP/JSON API
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.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 functionsnonoJava plugins
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenonoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnone infoRepcached, a Memcached patch, provides this functionallityyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononospark-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 configurationImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonooptimistic lockingoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesnoyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMnoyes
User concepts infoAccess controlAccess rights for users and roles on table levelyes infousing SASL (Simple Authentication and Security Layer) protocolAccess rights based on private key authentication or shared access signaturesyes

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KineticaMemcachedMicrosoft Azure Table StorageSolr
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