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

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

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonGeode  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.
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesCloud 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 modelDocument store
Key-value store
Key-value storeDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.92
Rank#131  Overall
#23  Key-value stores
Score7.85
Rank#51  Overall
#8  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitegeode.apache.orgfirebase.google.com/­products/­firestorespark.apache.org/­sql
Technical documentationgeode.apache.org/­docsfirebase.google.com/­docs/­firestorespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFatCloudOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.GoogleApache Software Foundation
Initial release2012200220172014
Current release1.1, February 20173.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses available as GemfirecommercialOpen 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 languageC#JavaScala
Server operating systemsWindowsAll OS with a Java VM infothe JDK (8 or later) is also requiredhostedLinux
OS X
Windows
Data schemeschema-freeschema-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.nonono
Secondary indexesyesnoyesno
SQL infoSupport of SQLno infoVia inetgration in SQL ServerSQL-like query language (OQL)noSQL-like DML and DDL statements
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Java Client API
Memcached protocol
RESTful HTTP API
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
Supported programming languagesC#.Net
All JVM based languages
C++
Groovy
Java
Scala
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infovia applicationsuser defined functionsyes, Firebase Rules & Cloud Functionsno
Triggersyes infovia applicationsyes infoCache Event Listenersyes, 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 nodesselectable replication factorMulti-source replicationMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoUsing Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyes, on a single nodeyesno
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.yesno
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAccess rights per client and object definableAccess 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
FatDBGeodeGoogle Cloud FirestoreSpark SQL
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