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DBMS > Apache Phoenix vs. EventStoreDB vs. Kingbase vs. Spark SQL

System Properties Comparison Apache Phoenix vs. EventStoreDB vs. Kingbase vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonEventStoreDB  Xexclude from comparisonKingbase  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseIndustrial-strength, open-source database solution built from the ground up for event sourcing.An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSEvent StoreRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score1.10
Rank#179  Overall
#1  Event Stores
Score0.45
Rank#262  Overall
#123  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitephoenix.apache.orgwww.eventstore.comwww.kingbase.com.cnspark.apache.org/­sql
Technical documentationphoenix.apache.orgdevelopers.eventstore.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationEvent Store LimitedBeiJing KINGBASE Information technologies inc.Apache Software Foundation
Initial release2014201219992014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 201921.2, February 2021V8.0, August 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open SourcecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and JavaScala
Server operating systemsLinux
Unix
Windows
Linux
Windows
Linux
Windows
Linux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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 indexesyesyesno
SQL infoSupport of SQLyesStandard with numerous extensionsSQL-like DML and DDL statements
APIs and other access methodsJDBCADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsuser defined functionsno
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by range, list and hash) and vertical partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesnone
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 Consistency
Foreign keys infoReferential integritynoyesno
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.yesno
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-standardno

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More resources
Apache PhoenixEventStoreDBKingbaseSpark SQL
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