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DBMS > Apache Phoenix vs. Databricks vs. Microsoft Azure AI Search

System Properties Comparison Apache Phoenix vs. Databricks vs. Microsoft Azure AI Search

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonDatabricks  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Search-as-a-service for web and mobile app development
Primary database modelRelational DBMSDocument store
Relational DBMS
Search engine
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.90
Rank#125  Overall
#59  Relational DBMS
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score5.75
Rank#58  Overall
#7  Search engines
Websitephoenix.apache.orgwww.databricks.comazure.microsoft.com/­en-us/­services/­search
Technical documentationphoenix.apache.orgdocs.databricks.comlearn.microsoft.com/­en-us/­azure/­search
DeveloperApache Software FoundationDatabricksMicrosoft
Initial release201420132015
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019V1
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava
Server operating systemsLinux
Unix
Windows
hostedhosted
Data schemeyes infolate-bound, schema-on-read capabilitiesFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesyes
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 indexesyesyesyes
SQL infoSupport of SQLyeswith Databricks SQLno
APIs and other access methodsJDBCJDBC
ODBC
RESTful HTTP API
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Python
R
Scala
C#
Java
JavaScript
Python
Server-side scripts infoStored proceduresuser defined functionsuser defined functions and aggregatesno
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesyes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
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.yesnono
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyyes infousing Azure authentication
More information provided by the system vendor
Apache PhoenixDatabricksMicrosoft Azure AI Search
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Apache PhoenixDatabricksMicrosoft Azure AI Search
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