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DBMS > Druid vs. Kinetica

System Properties Comparison Druid vs. Kinetica

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Editorial information provided by DB-Engines
NameDruid  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionOpen-source analytics data store designed for OLAP queries on timeseries dataGPU-accelerated database for real-time analysis of large and streaming datasets
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.95
Rank#119  Overall
#57  Relational DBMS
#8  Time Series DBMS
Score0.61
Rank#197  Overall
#95  Relational DBMS
Websitedruid.apache.orgwww.kinetica.com
Technical documentationdruid.apache.org/­docs/­latest/­designwww.kinetica.com/­docs
DeveloperMetamarkets Group and contributorsKinetica
Initial release20122012
Current release6.0
License infoCommercial or Open SourceOpen Source infoApache license v2commercial
Cloud-based only infoOnly available as a cloud servicenono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, C++
Server operating systemsLinux
OS X
Unix
Linux
Data schemeyes infoschema-less columns are supportedyes
Typing infopredefined data types such as float or dateyesyes
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.nono
Secondary indexesyesyes
SQL infoSupport of SQLSQL support via Apache Calcite adapterSQL-like DML and DDL statements
APIs and other access methodsJSON over HTTPJDBC
ODBC
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnouser defined functions
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMaster-slave replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAM
User concepts infoAccess controlno infoavailable via extensionsAccess rights for users and roles on table level

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More resources
DruidKinetica
Recent citations in the news

Introducing Apache Druid
17 January 2020, insideBIGDATA

Druid Developer Expands Query Options
17 April 2020, Datanami

Druid Developer Ramps Cloud-Native Approach
10 December 2019, Datanami

Real-Time Analytics from Your Data Lake Teaching the Elephant to Dance
21 January 2020, insideBIGDATA

Imply launches with $2M to commercialize the Druid open-source data store
19 October 2015, VentureBeat

provided by Google News

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22 May 2020, Cole of Duty

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2 June 2020, Bulletin Line

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COVID-19 Impact on Global GPU Database Industry 2020: Market Analysis by Size, Share, Trends, SWOT Analysis by Top Key Players and Forecast Research to 2025
2 June 2020, News Distinct

provided by Google News

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