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DBMS > Apache Phoenix vs. Geode vs. Microsoft Azure AI Search vs. Spark SQL

System Properties Comparison Apache Phoenix vs. Geode vs. Microsoft Azure AI Search vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGeode  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseGeode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesSearch-as-a-service for web and mobile app developmentSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSKey-value storeSearch engineRelational DBMS
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score1.92
Rank#131  Overall
#23  Key-value stores
Score5.59
Rank#63  Overall
#7  Search engines
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitephoenix.apache.orggeode.apache.orgazure.microsoft.com/­en-us/­services/­searchspark.apache.org/­sql
Technical documentationphoenix.apache.orggeode.apache.org/­docslearn.microsoft.com/­en-us/­azure/­searchspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.MicrosoftApache Software Foundation
Initial release2014200220152014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20191.1, February 2017V13.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2; commercial licenses available as GemfirecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaScala
Server operating systemsLinux
Unix
Windows
All OS with a Java VM infothe JDK (8 or later) is also requiredhostedLinux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeyesyes
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.nononono
Secondary indexesyesnoyesno
SQL infoSupport of SQLyesSQL-like query language (OQL)noSQL-like DML and DDL statements
APIs and other access methodsJDBCJava Client API
Memcached protocol
RESTful HTTP API
RESTful HTTP APIJDBC
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
All JVM based languages
C++
Groovy
Java
Scala
C#
Java
JavaScript
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsuser defined functionsnono
Triggersnoyes infoCache Event Listenersnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replicationyes infoImplicit feature of the cloud servicenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes, on a single nodenono
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.yesyesnono
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights per client and object definableyes infousing Azure authenticationno

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More resources
Apache PhoenixGeodeMicrosoft Azure AI SearchSpark SQL
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