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DBMS > Apache Pinot vs. HEAVY.AI vs. Microsoft Azure Data Explorer vs. SpatiaLite

System Properties Comparison Apache Pinot vs. HEAVY.AI vs. Microsoft Azure Data Explorer vs. SpatiaLite

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSpatiaLite  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareFully managed big data interactive analytics platformSpatial extension of SQLite
Primary database modelRelational DBMSRelational DBMSRelational DBMS infocolumn orientedSpatial DBMS
Secondary database modelsSpatial DBMSDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.40
Rank#270  Overall
#125  Relational DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score1.60
Rank#149  Overall
#3  Spatial DBMS
Websitepinot.apache.orggithub.com/­heavyai/­heavydb
www.heavy.ai
azure.microsoft.com/­services/­data-explorerwww.gaia-gis.it/­fossil/­libspatialite/­index
Technical documentationdocs.pinot.apache.orgdocs.heavy.aidocs.microsoft.com/­en-us/­azure/­data-explorerwww.gaia-gis.it/­gaia-sins/­spatialite_topics.html
DeveloperApache Software Foundation and contributorsHEAVY.AI, Inc.MicrosoftAlessandro Furieri
Initial release2015201620192008
Current release1.0.0, September 20235.10, January 2022cloud service with continuous releases5.0.0, August 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2; enterprise edition availablecommercialOpen Source infoMPL 1.1, GPL v2.0 or LGPL v2.1
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++ and CUDAC++
Server operating systemsAll OS with a Java JDK11 or higherLinuxhostedserver-less
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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.noyesno
Secondary indexesnoall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query languageyesKusto Query Language (KQL), SQL subsetyes
APIs and other access methodsJDBCJDBC
ODBC
Thrift
Vega
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesGo
Java
Python
All languages supporting JDBC/ODBC/Thrift
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, Rno
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding infoRound robinSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID
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.yesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAzure Active Directory Authenticationno

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More resources
Apache PinotHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Microsoft Azure Data ExplorerSpatiaLite
DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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Recent citations in the news

Real-Time Analytics for Mobile App Crashes using Apache Pinot
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Speed of Apache Pinot at the Cost of Cloud Object Storage with Tiered Storage
16 August 2023, InfoQ.com

StarTree Announces Integration between Apache Pinot and Delta Lake with StarTree Cloud
20 June 2023, Datanami

StarTree brings Apache Pinot real-time database to the cloud
22 March 2022, TechTarget

Data analytics startup StarTree secures cash to expand its Apache Pinot-powered platform
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19 April 2023, Business Wire

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14 April 2023, InfoWorld

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Azure Data Explorer: Log and telemetry analytics benchmark
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