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DBMS > Apache Phoenix vs. Elasticsearch vs. Google Cloud Firestore vs. Postgres-XL vs. Spark SQL

System Properties Comparison Apache Phoenix vs. Elasticsearch vs. Google Cloud Firestore vs. Postgres-XL vs. Spark SQL

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonElasticsearch  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA 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 metricCloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.Based on PostgreSQL enhanced with MPP and write-scale-out cluster featuresSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSSearch engineDocument storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score132.83
Rank#7  Overall
#1  Search engines
Score7.36
Rank#53  Overall
#9  Document stores
Score0.53
Rank#254  Overall
#117  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitephoenix.apache.orgwww.elastic.co/­elasticsearchfirebase.google.com/­products/­firestorewww.postgres-xl.orgspark.apache.org/­sql
Technical documentationphoenix.apache.orgwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlfirebase.google.com/­docs/­firestorewww.postgres-xl.org/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationElasticGoogleApache Software Foundation
Initial release2014201020172014 infosince 2012, originally named StormDB2014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20198.6, January 202310 R1, October 20183.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoElastic LicensecommercialOpen Source infoMozilla public licenseOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaCScala
Server operating systemsLinux
Unix
Windows
All OS with a Java VMhostedLinux
macOS
Linux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-free infoFlexible type definitions. Once a type is defined, it is persistentschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nononoyes infoXML type, but no XML query functionalityno
Secondary indexesyesyes infoAll search fields are automatically indexedyesyesno
SQL infoSupport of SQLyesSQL-like query languagenoyes infodistributed, parallel query executionSQL-like DML and DDL statements
APIs and other access methodsJDBCJava API
RESTful HTTP/JSON API
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyesyes, Firebase Rules & Cloud Functionsuser defined functionsno
Triggersnoyes infoby using the 'percolation' featureyes, with Cloud Functionsyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardinghorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationES-Hadoop ConnectorUsing Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoyesACID infoMVCCno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesMemcached and Redis integrationnono
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.fine grained access rights according to SQL-standardno

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Apache PhoenixElasticsearchGoogle Cloud FirestorePostgres-XLSpark SQL
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