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DBMS > Apache Phoenix vs. Cloudflare Workers KV vs. EventStoreDB vs. Spark SQL

System Properties Comparison Apache Phoenix vs. Cloudflare Workers KV vs. EventStoreDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonCloudflare Workers KV  Xexclude from comparisonEventStoreDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.Industrial-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
Score0.32
Rank#283  Overall
#40  Key-value stores
Score1.10
Rank#179  Overall
#1  Event Stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitephoenix.apache.orgwww.cloudflare.com/­developer-platform/­workers-kvwww.eventstore.comspark.apache.org/­sql
Technical documentationphoenix.apache.orgdevelopers.cloudflare.com/­kv/­apidevelopers.eventstore.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationCloudflareEvent Store LimitedApache Software Foundation
Initial release2014201820122014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 201921.2, February 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScala
Server operating systemsLinux
Unix
Windows
hostedLinux
Windows
Linux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeyes
Typing infopredefined data types such as float or dateyesnoyes
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 methodsJDBCHTTP REST
Proprietary protocol
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsnono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, 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 ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono
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-tenancyno

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More resources
Apache PhoenixCloudflare Workers KVEventStoreDBSpark SQL
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