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DBMS > Apache Pinot vs. Hawkular Metrics vs. Percona Server for MongoDB vs. Spark SQL

System Properties Comparison Apache Pinot vs. Hawkular Metrics vs. Percona Server for MongoDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonPercona Server for MongoDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A drop-in replacement for MongoDB Community Edition with enterprise-grade features.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSTime Series DBMSDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.38
Rank#275  Overall
#126  Relational DBMS
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score0.60
Rank#246  Overall
#39  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitepinot.apache.orgwww.hawkular.orgwww.percona.com/­mongodb/­software/­percona-server-for-mongodbspark.apache.org/­sql
Technical documentationdocs.pinot.apache.orgwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.percona.com/­percona-distribution-for-mongodbspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation and contributorsCommunity supported by Red HatPerconaApache Software Foundation
Initial release2015201420152014
Current release1.0.0, September 20233.4.10-2.10, November 20173.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoGPL Version 2Open 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 languageJavaJavaC++Scala
Server operating systemsAll OS with a Java JDK11 or higherLinux
OS X
Windows
LinuxLinux
OS X
Windows
Data schemeyesschema-freeschema-freeyes
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 indexesnoyesno
SQL infoSupport of SQLSQL-like query languagenonoSQL-like DML and DDL statements
APIs and other access methodsJDBCHTTP RESTproprietary protocol using JSONJDBC
ODBC
Supported programming languagesGo
Java
Python
Go
Java
Python
Ruby
Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoJavaScriptno
Triggersyes infovia Hawkular Alertingnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding infobased on CassandraShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on CassandraSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
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.noyes infovia In-Memory Engineno
User concepts infoAccess controlnoAccess rights for users and rolesno

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Apache PinotHawkular MetricsPercona Server for MongoDBSpark SQL
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