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DBMS > Apache Druid vs. Kinetica vs. Pinecone

System Properties Comparison Apache Druid vs. Kinetica vs. Pinecone

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonKinetica  Xexclude from comparisonPinecone  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 CPUsA managed, cloud-native vector database
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSVector DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score3.23
Rank#92  Overall
#3  Vector DBMS
Websitedruid.apache.orgwww.kinetica.comwww.pinecone.io
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.kinetica.comdocs.pinecone.io/­docs/­overview
DeveloperApache Software Foundation and contributorsKineticaPinecone Systems, Inc
Initial release201220122019
Current release29.0.1, April 20247.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++
Server operating systemsLinux
OS X
Unix
Linuxhosted
Data schemeyes infoschema-less columns are supportedyes
Typing infopredefined data types such as float or dateyesyesString, Number, Boolean
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.nonono
Secondary indexesyesyes
SQL infoSupport of SQLSQL for queryingSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
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 methodsnonono
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 datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAMno
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

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More resources
Apache DruidKineticaPinecone
DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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