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

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

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonSpark SQL  Xexclude from comparisonVoltDB  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.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 processingDistributed In-Memory NewSQL RDBMS infoUsed for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory
Primary database modelDocument store
Key-value store
Document storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.96
Rank#48  Overall
#8  Document stores
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score1.46
Rank#159  Overall
#74  Relational DBMS
Websitefirebase.google.com/­products/­firestorespark.apache.org/­sqlwww.voltdb.com
Technical documentationfirebase.google.com/­docs/­firestorespark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.voltdb.com
DeveloperFatCloudGoogleApache Software FoundationVoltDB Inc.
Initial release2012201720142010
Current release3.5.0 ( 2.13), September 202311.3, April 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoAGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#ScalaJava, C++
Server operating systemsWindowshostedLinux
OS X
Windows
Linux
OS X infofor development
Data schemeschema-freeschema-freeyesyes
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.nono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLno infoVia inetgration in SQL ServernoSQL-like DML and DDL statementsyes infoonly a subset of SQL 99
APIs and other access methods.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
Java API
JDBC
RESTful HTTP/JSON API
Supported programming languagesC#Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
Java
Python
R
Scala
C#
C++
Erlang infonot officially supported
Go
Java
JavaScript infoNode.js
PHP
Python
Server-side scripts infoStored proceduresyes infovia applicationsyes, Firebase Rules & Cloud FunctionsnoJava
Triggersyes infovia applicationsyes, with Cloud Functionsnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replicationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesUsing Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono infoFOREIGN KEY constraints are not supported
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnoACID infoTransactions are executed single-threaded within stored procedures
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoData access is serialized by the server
Durability infoSupport for making data persistentyesyesyesyes infoSnapshots and command logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlno 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.noUsers and roles with access to stored procedures

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More resources
FatDBGoogle Cloud FirestoreSpark SQLVoltDB
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