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DBMS > Apache Pinot vs. Kinetica vs. Pinecone

System Properties Comparison Apache Pinot vs. Kinetica vs. Pinecone

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonKinetica  Xexclude from comparisonPinecone  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyFully vectorized database across both GPUs and CPUsA managed, cloud-native vector database
Primary database modelRelational DBMSRelational DBMSVector DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.35
Rank#274  Overall
#128  Relational DBMS
Score0.42
Rank#261  Overall
#120  Relational DBMS
Score3.02
Rank#87  Overall
#3  Vector DBMS
Websitepinot.apache.orgwww.kinetica.comwww.pinecone.io
Technical documentationdocs.pinot.apache.orgdocs.kinetica.comdocs.pinecone.io/­docs/­overview
DeveloperApache Software Foundation and contributorsKineticaPinecone Systems, Inc
Initial release201520122019
Current release1.0.0, September 20237.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial
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 systemsAll OS with a Java JDK11 or higherLinuxhosted
Data schemeyesyes
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.nono
Secondary indexesyes
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statementsno
APIs and other access methodsJDBCJDBC
ODBC
RESTful HTTP API
RESTful HTTP API
Supported programming languagesGo
Java
Python
C++
Java
JavaScript (Node.js)
Python
Python
Server-side scripts infoStored proceduresuser defined functions
Triggersyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano
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.yes infoGPU vRAM or System RAMno
User concepts infoAccess controlAccess rights for users and roles on table level

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More resources
Apache PinotKineticaPinecone
DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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