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DBMS > Apache Pinot vs. Kinetica

System Properties Comparison Apache Pinot vs. Kinetica

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Our visitors often compare Apache Pinot and Kinetica with Snowflake, HEAVY.AI and TimescaleDB.

Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyFully vectorized database across both GPUs and CPUs
Primary database modelRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.40
Rank#270  Overall
#125  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websitepinot.apache.orgwww.kinetica.com
Technical documentationdocs.pinot.apache.orgdocs.kinetica.com
DeveloperApache Software Foundation and contributorsKinetica
Initial release20152012
Current release1.0.0, September 20237.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial
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 systemsAll OS with a Java JDK11 or higherLinux
Data schemeyesyes
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.no
Secondary indexesyes
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsJDBCJDBC
ODBC
RESTful HTTP API
Supported programming languagesGo
Java
Python
C++
Java
JavaScript (Node.js)
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 methodsno
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 datayes
Durability infoSupport for making data persistentyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users and roles on table level

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More resources
Apache PinotKinetica
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