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DBMS > Apache Phoenix vs. Cloudflare Workers KV vs. Elasticsearch

System Properties Comparison Apache Phoenix vs. Cloudflare Workers KV vs. Elasticsearch

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonCloudflare Workers KV  Xexclude from comparisonElasticsearch  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.A distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric
Primary database modelRelational DBMSKey-value storeSearch engine
Vector DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.90
Rank#121  Overall
#59  Relational DBMS
Score0.29
Rank#288  Overall
#42  Key-value stores
Score132.32
Rank#8  Overall
#1  Search engines
#1  Vector DBMS
Websitephoenix.apache.orgwww.cloudflare.com/­developer-platform/­workers-kvwww.elastic.co/­elasticsearch
Technical documentationphoenix.apache.orgdevelopers.cloudflare.com/­kv/­apiwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.html
DeveloperApache Software FoundationCloudflareElastic
Initial release201420182010
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20198.6, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoElastic License
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava
Server operating systemsLinux
Unix
Windows
hostedAll OS with a Java VM
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeschema-free infoFlexible type definitions. Once a type is defined, it is persistent
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 indexesyesnoyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyesnoSQL-like query language
APIs and other access methodsJDBCHTTP REST
Proprietary protocol
Java API
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsnoyes
Triggersnonoyes infoby using the 'percolation' feature
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnoES-Hadoop Connector
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyEventual ConsistencyEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all
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.yesnoMemcached and Redis integration
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

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