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DBMS > Apache Phoenix vs. FatDB vs. Google Cloud Firestore vs. Quasardb vs. Spark SQL

System Properties Comparison Apache Phoenix vs. FatDB vs. Google Cloud Firestore vs. Quasardb vs. Spark SQL

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonQuasardb  Xexclude from comparisonSpark SQL  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA .NET NoSQL DBMS that can integrate with and extend SQL Server.Cloud 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.Distributed, high-performance timeseries databaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSDocument store
Key-value store
Document storeTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score7.85
Rank#51  Overall
#8  Document stores
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitephoenix.apache.orgfirebase.google.com/­products/­firestorequasar.aispark.apache.org/­sql
Technical documentationphoenix.apache.orgfirebase.google.com/­docs/­firestoredoc.quasar.ai/­masterspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationFatCloudGooglequasardbApache Software Foundation
Initial release20142012201720092014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20193.14.1, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC#C++Scala
Server operating systemsLinux
Unix
Windows
WindowshostedBSD
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes infointeger and binaryyes
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.nononono
Secondary indexesyesyesyesyes infowith tagsno
SQL infoSupport of SQLyesno infoVia inetgration in SQL ServernoSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsJDBC.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
HTTP APIJDBC
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C#Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyes infovia applicationsyes, Firebase Rules & Cloud Functionsnono
Triggersnoyes infovia applicationsyes, with Cloud Functionsnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infoconsistent hashingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
selectable replication factorMulti-source replicationSource-replica replication with selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyesUsing Cloud Dataflowwith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoyesACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using LevelDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoTransient modeno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyno infoCan implement custom security layer via applicationsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.Cryptographically strong user authentication and audit trailno

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More resources
Apache PhoenixFatDBGoogle Cloud FirestoreQuasardbSpark SQL
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