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DBMS > Apache Pinot vs. Rockset vs. Spark SQL

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

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonRockset  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyA scalable, reliable search and analytics service in the cloud, built on RocksDBSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSDocument storeRelational DBMS
Secondary database modelsRelational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.40
Rank#270  Overall
#125  Relational DBMS
Score0.79
Rank#211  Overall
#35  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitepinot.apache.orgrockset.comspark.apache.org/­sql
Technical documentationdocs.pinot.apache.orgdocs.rockset.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation and contributorsRocksetApache Software Foundation
Initial release201520192014
Current release1.0.0, September 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++Scala
Server operating systemsAll OS with a Java JDK11 or higherhostedLinux
OS X
Windows
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesdynamic typingyes
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 infoingestion from XML files supportedno
Secondary indexesall fields are automatically indexedno
SQL infoSupport of SQLSQL-like query languageRead-only SQL queries, including JOINsSQL-like DML and DDL statements
APIs and other access methodsJDBCHTTP RESTJDBC
ODBC
Supported programming languagesGo
Java
Python
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningAutomatic shardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono
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.no
User concepts infoAccess controlAccess rights for users and organizations can be defined via Rockset consoleno

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More resources
Apache PinotRocksetSpark SQL
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