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DBMS > Apache Phoenix vs. Greenplum vs. Microsoft Azure Data Explorer vs. Yanza

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

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGreenplum  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 HBaseAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.Fully managed big data interactive analytics platformTime Series DBMS for IoT Applications
Primary database modelRelational DBMSRelational DBMSRelational DBMS infocolumn orientedTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
Document 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
Score8.37
Rank#48  Overall
#30  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitephoenix.apache.orggreenplum.orgazure.microsoft.com/­services/­data-exploreryanza.com
Technical documentationphoenix.apache.orgdocs.greenplum.orgdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software FoundationPivotal Software Inc.MicrosoftYanza
Initial release2014200520192015
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20197.0.0, September 2023cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0commercialcommercial 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 languageJava
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.noyes infosince Version 4.2yesno
Secondary indexesyesyesall fields are automatically indexedno
SQL infoSupport of SQLyesyesKusto Query Language (KQL), SQL subsetno
APIs and other access methodsJDBCJDBC
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
Java
Perl
Python
R
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
any language that supports HTTP calls
Server-side scripts infoStored proceduresuser defined functionsyesYes, possible languages: KQL, Python, Rno
Triggersnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica 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 integrationyesSpark 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 integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnono
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.yesnono
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 PhoenixGreenplumMicrosoft Azure Data ExplorerYanza
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