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DBMS > Apache Druid vs. Kinetica

System Properties Comparison Apache Druid vs. Kinetica

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataFully vectorized database across both GPUs and CPUs
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.07
Rank#116  Overall
#57  Relational DBMS
#8  Time Series DBMS
Score0.84
Rank#253  Overall
#117  Relational DBMS
Websitedruid.apache.orgwww.kinetica.com
Technical documentationdruid.apache.org/­docs/­latest/­designwww.kinetica.com/­docs
DeveloperApache Software Foundation and contributorsKinetica
Initial release20122012
Current release26.0.0, May 20237.1, August 2021
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

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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 for queryingSQL-like DML and DDL statements
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
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 nodesSharding infomanual/auto, time-basedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesSource-replica 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 controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users and roles on table level
More information provided by the system vendor
Apache DruidKinetica
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
Apache DruidKinetica
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