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

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

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonEhcache  Xexclude from comparisonEventStoreDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA widely adopted Java cache with tiered storage optionsIndustrial-strength, open-source database solution built from the ground up for event sourcing.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSKey-value storeEvent StoreRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score4.89
Rank#67  Overall
#8  Key-value stores
Score1.10
Rank#179  Overall
#1  Event Stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitephoenix.apache.orgwww.ehcache.orgwww.eventstore.comspark.apache.org/­sql
Technical documentationphoenix.apache.orgwww.ehcache.org/­documentationdevelopers.eventstore.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationTerracotta Inc, owned by Software AGEvent Store LimitedApache Software Foundation
Initial release2014200920122014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20193.10.0, March 202221.2, February 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2; commercial licenses availableOpen SourceOpen 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 languageJavaJavaScala
Server operating systemsLinux
Unix
Windows
All OS with a Java VMLinux
Windows
Linux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeyes
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.nonono
Secondary indexesyesnono
SQL infoSupport of SQLyesnoSQL-like DML and DDL statements
APIs and other access methodsJDBCJCacheJDBC
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
JavaJava
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsnono
Triggersnoyes infoCache Event Listenersno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoby using Terracotta Serveryes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yes infoby using Terracotta Servernone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyTunable Consistency (Strong, Eventual, Weak)
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes infosupports JTA and can work as an XA resourceno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infousing a tiered cache-storage approachyes
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-tenancynono

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More resources
Apache PhoenixEhcacheEventStoreDBSpark SQL
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