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DBMS > Apache Phoenix vs. HEAVY.AI vs. Microsoft Azure Data Explorer vs. Yanza

System Properties Comparison Apache Phoenix vs. HEAVY.AI vs. Microsoft Azure Data Explorer vs. Yanza

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareFully managed big data interactive analytics platformTime Series DBMS for IoT Applications
Primary database modelRelational DBMSRelational DBMSRelational DBMS infocolumn orientedTime Series 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitephoenix.apache.orggithub.com/­heavyai/­heavydb
www.heavy.ai
azure.microsoft.com/­services/­data-exploreryanza.com
Technical documentationphoenix.apache.orgdocs.heavy.aidocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software FoundationHEAVY.AI, Inc.MicrosoftYanza
Initial release2014201620192015
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20195.10, January 2022cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2; enterprise edition availablecommercialcommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenonoyesno infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++ and CUDA
Server operating systemsLinux
Unix
Windows
LinuxhostedWindows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesFixed schema with schema-less datatypes (dynamic)schema-free
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-typesno
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.nonoyesno
Secondary indexesyesnoall fields are automatically indexedno
SQL infoSupport of SQLyesyesKusto Query Language (KQL), SQL subsetno
APIs and other access methodsJDBCJDBC
ODBC
Thrift
Vega
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
All languages supporting JDBC/ODBC/Thrift
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
any language that supports HTTP calls
Server-side scripts infoStored proceduresuser defined functionsnoYes, possible languages: KQL, Python, Rno
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoRound robinSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-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 methodsHadoop integrationnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyfine grained access rights according to SQL-standardAzure Active Directory Authenticationno

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More resources
Apache PhoenixHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Microsoft Azure Data ExplorerYanza
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