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DBMS > Citus vs. FatDB vs. Google Cloud Firestore vs. Spark SQL

System Properties Comparison Citus vs. FatDB vs. Google Cloud Firestore vs. Spark SQL

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Firestore  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.
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLA .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.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSDocument store
Key-value store
Document storeRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.15
Rank#123  Overall
#60  Relational DBMS
Score8.96
Rank#48  Overall
#8  Document stores
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitewww.citusdata.comfirebase.google.com/­products/­firestorespark.apache.org/­sql
Technical documentationdocs.citusdata.comfirebase.google.com/­docs/­firestorespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFatCloudGoogleApache Software Foundation
Initial release2010201220172014
Current release8.1, December 20183.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC#Scala
Server operating systemsLinuxWindowshostedLinux
OS X
Windows
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.yes infospecific XML type available, but no XML query functionalitynono
Secondary indexesyesyesyesno
SQL infoSupport of SQLyes infostandard, with numerous extensionsno infoVia inetgration in SQL ServernoSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes infovia applicationsyes, Firebase Rules & Cloud Functionsno
Triggersyesyes infovia applicationsyes, with Cloud Functionsno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsselectable replication factorMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesUsing Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoyesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlfine grained access rights according to SQL-standardno 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.no

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More resources
CitusFatDBGoogle Cloud FirestoreSpark SQL
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