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

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

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonKinetica  Xexclude from comparisonSolr  Xexclude from comparisonSpatiaLite  Xexclude from comparisonTerarkDB  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 SQLiteA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelRelational DBMSRelational DBMSSearch engineSpatial DBMSKey-value store
Secondary database modelsSpatial DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.73
Rank#204  Overall
#99  Relational DBMS
Score53.85
Rank#22  Overall
#3  Search engines
Score1.95
Rank#128  Overall
#2  Spatial DBMS
Score0.01
Rank#344  Overall
#54  Key-value stores
Websitewww.kinetica.comlucene.apache.org/­solrwww.gaia-gis.it/­fossil/­libspatialite/­indexgithub.com/­Terark/­terarkdb
Technical documentationwww.kinetica.com/­docslucene.apache.org/­solr/­resources.htmlwww.gaia-gis.it/­gaia-sins/­spatialite_topics.htmlgithub.com/­Terark/­terarkdb/­wiki
DeveloperDrizzle project, originally started by Brian AkerKineticaApache Software FoundationAlessandro FurieriTerark
Initial release20082012200620082016
Current release7.2.4, September 20127.1, August 20218.11.0, November 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 v2.1commercial inforestricted open source version available
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, C++JavaC++C++
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 fieldsyesschema-free
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typingyesno
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.noyesnono
Secondary indexesyesyesyes infoAll search fields are automatically indexedyesno
SQL infoSupport of SQLyes infowith proprietary extensionsSQL-like DML and DDL statementsSolr Parallel SQL Interfaceyesno
APIs and other access methodsJDBCJDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
C++ API
Java 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
C++
Java
Server-side scripts infoStored proceduresnouser defined functionsJava pluginsnono
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 changesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Foreign keys infoReferential integrityyesyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnooptimistic lockingACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
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 controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users and roles on table levelyesnono
More information provided by the system vendor
DrizzleKineticaSolrSpatiaLiteTerarkDB
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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More resources
DrizzleKineticaSolrSpatiaLiteTerarkDB
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