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DBMS > Apache Pinot vs. Kinetica vs. Kyligence Enterprise vs. Spark SQL

System Properties Comparison Apache Pinot vs. Kinetica vs. Kyligence Enterprise vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonKinetica  Xexclude from comparisonKyligence Enterprise  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyFully vectorized database across both GPUs and CPUsA distributed analytics engine for big data, built on top of Apache KylinSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSRelational 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
Score0.40
Rank#269  Overall
#124  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitepinot.apache.orgwww.kinetica.comkyligence.io/­kyligence-enterprisespark.apache.org/­sql
Technical documentationdocs.pinot.apache.orgdocs.kinetica.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation and contributorsKineticaKyligence, Inc.Apache Software Foundation
Initial release2015201220162014
Current release1.0.0, September 20237.1, August 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++JavaScala
Server operating systemsAll OS with a Java JDK11 or higherLinuxLinuxLinux
OS X
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesyesyesno
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statementsANSI SQL for queries (using Apache Calcite)SQL-like DML and DDL statements
APIs and other access methodsJDBCJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languagesGo
Java
Python
C++
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsno
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesno
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.yes infoGPU vRAM or System RAMnono
User concepts infoAccess controlAccess rights for users and roles on table levelno

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More resources
Apache PinotKineticaKyligence EnterpriseSpark SQL
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