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

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

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSpark SQL  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseCloud 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 processingWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelRelational DBMSDocument storeRelational DBMSRelational DBMSObject oriented DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score7.36
Rank#53  Overall
#9  Document stores
Score0.53
Rank#254  Overall
#117  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.10
Rank#356  Overall
#16  Object oriented DBMS
Websitephoenix.apache.orgfirebase.google.com/­products/­firestorewww.postgres-xl.orgspark.apache.org/­sqlwakanda.github.io
Technical documentationphoenix.apache.orgfirebase.google.com/­docs/­firestorewww.postgres-xl.org/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwakanda.github.io/­doc
DeveloperApache Software FoundationGoogleApache Software FoundationWakanda SAS
Initial release201420172014 infosince 2012, originally named StormDB20142012
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 201910 R1, October 20183.5.0 ( 2.13), September 20232.7.0 (AprilĀ 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoMozilla public licenseOpen Source infoApache 2.0Open Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCScalaC++, JavaScript
Server operating systemsLinux
Unix
Windows
hostedLinux
macOS
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeyesyesyes
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.nonoyes infoXML type, but no XML query functionalitynono
Secondary indexesyesyesyesno
SQL infoSupport of SQLyesnoyes infodistributed, parallel query executionSQL-like DML and DDL statementsno
APIs and other access methodsJDBCAndroid
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
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
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
JavaScript
Server-side scripts infoStored proceduresuser defined functionsyes, Firebase Rules & Cloud Functionsuser defined functionsnoyes
Triggersnoyes, with Cloud Functionsyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioningyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationUsing Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesACID infoMVCCnoACID
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.yesnonono
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-standardnoyes

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More resources
Apache PhoenixGoogle Cloud FirestorePostgres-XLSpark SQLWakandaDB
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