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DBMS > Kinetica vs. Lovefield vs. SiteWhere vs. Solr vs. Yaacomo

System Properties Comparison Kinetica vs. Lovefield vs. SiteWhere vs. Solr vs. Yaacomo

Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonLovefield  Xexclude from comparisonSiteWhere  Xexclude from comparisonSolr  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionFully vectorized database across both GPUs and CPUsEmbeddable relational database for web apps written in pure JavaScriptM2M integration platform for persisting/querying time series dataA widely used distributed, scalable search engine based on Apache LuceneOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSRelational DBMSTime Series 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
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.33
Rank#286  Overall
#131  Relational DBMS
Score0.06
Rank#383  Overall
#43  Time Series DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websitewww.kinetica.comgoogle.github.io/­lovefieldgithub.com/­sitewhere/­sitewheresolr.apache.orgyaacomo.com
Technical documentationdocs.kinetica.comgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdsitewhere1.sitewhere.io/­index.htmlsolr.apache.org/­resources.html
DeveloperKineticaGoogleSiteWhereApache Software FoundationQ2WEB GmbH
Initial release20122014201020062009
Current release7.1, August 20212.1.12, February 20179.6.1, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoCommon Public Attribution License Version 1.0Open Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++JavaScriptJavaJava
Server operating systemsLinuxserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariLinux
OS X
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Android
Linux
Windows
Data schemeyesyespredefined schemeyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyesyesyes 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.nononoyesno
Secondary indexesyesyesnoyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language infovia JavaScript builder patternnoSolr Parallel SQL Interfaceyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HTTP RESTJava API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
JavaScript.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 functionsnoJava plugins
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeUsing read-only observersyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infobased on HBaseShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneselectable replication factor infobased on HBaseyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononospark-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 configurationImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnooptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMyes infousing MemoryDBnoyesyes
User concepts infoAccess controlAccess rights for users and roles on table levelnoUsers with fine-grained authorization conceptyesfine grained access rights according to SQL-standard

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More resources
KineticaLovefieldSiteWhereSolrYaacomo
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