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DBMS > Apache Pinot vs. OrigoDB vs. Spark SQL

System Properties Comparison Apache Pinot vs. OrigoDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonOrigoDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyA fully ACID in-memory object graph databaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSDocument store
Object oriented DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.38
Rank#275  Overall
#126  Relational DBMS
Score0.06
Rank#380  Overall
#50  Document stores
#19  Object oriented DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitepinot.apache.orgorigodb.comspark.apache.org/­sql
Technical documentationdocs.pinot.apache.orgorigodb.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation and contributorsRobert Friberg et alApache Software Foundation
Initial release20152009 infounder the name LiveDB2014
Current release1.0.0, September 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC#Scala
Server operating systemsAll OS with a Java JDK11 or higherLinux
Windows
Linux
OS X
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesUser defined using .NET types and collectionsyes
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 infocan be achieved using .NETno
Secondary indexesyesno
SQL infoSupport of SQLSQL-like query languagenoSQL-like DML and DDL statements
APIs and other access methodsJDBC.NET Client API
HTTP API
LINQ
JDBC
ODBC
Supported programming languagesGo
Java
Python
.NetJava
Python
R
Scala
Server-side scripts infoStored proceduresyesno
Triggersyes infoDomain Eventsno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioninghorizontal partitioning infoclient side managed; servers are not synchronizedyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno
Foreign keys infoReferential integritydepending on modelno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyes infoWrite ahead logyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlRole based authorizationno

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More resources
Apache PinotOrigoDBSpark SQL
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