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

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

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonHarperDB  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.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.A distributed database focused on speed and ease of use. It has an intuitive REST API, and supports NoSQL and SQL including joins. HarperDB leverages standard interfaces, and users can be up and running in minutes.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Document storeDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score9.32
Rank#52  Overall
#10  Document stores
Score0.52
Rank#238  Overall
#37  Document stores
Score22.86
Rank#35  Overall
#21  Relational DBMS
Websitefirebase.google.com/­products/­firestoreharperdb.iospark.apache.org/­sql
Technical documentationfirebase.google.com/­docs/­firestoreharperdb.io/­developers/­documentation/­overviewspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFatCloudGoogleHarperDBApache Software Foundation
Initial release2012201720172014
Current release3.1, August 20213.2.0, October 2021
License infoCommercial or Open Sourcecommercialcommercialcommercial infofree community edition availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#Node.jsScala
Server operating systemsWindowshostedLinux
OS X
Linux
OS X
Windows
Data schemeschema-freeschema-freedynamic schemayes
Typing infopredefined data types such as float or dateyesyesyes infoJSON data typesyes
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 indexesyesyesyesno
SQL infoSupport of SQLno infoVia inetgration in SQL ServernoSQL-like data manipulation statementsSQL-like DML and DDL statements
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
React Hooks
RESTful HTTP/JSON API
WebSocket
JDBC
ODBC
Supported programming languagesC#Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infovia applicationsyes, Firebase Rules & Cloud FunctionsCustom Functions infosince release 3.1no
Triggersyes infovia applicationsyes, with Cloud Functionsnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingA table resides as a whole on one (or more) nodes in a clusteryes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replicationyes infothe nodes on which a table resides can be definednone
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesAtomic execution of specific operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes, using LMDByes
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 for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.Access rights for users and rolesno
More information provided by the system vendor
FatDBGoogle Cloud FirestoreHarperDBSpark SQL
Specific characteristicsHarperDB is the first distributed database with hybrid SQL & NoSQL functionality...
» more
Competitive advantagesBy combining the functionality of the best SQL, NoSQL, and NewSQL products on the...
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Typical application scenariosUse cases where HarperDB is a better fit than other solutions include: Rapid app...
» more
Key customersA few highlighted customers include: US Army, US Airforce, Chelan PUD, TATA, & Lumen....
» more
Market metricsOver 26K total HarperDB users : 12,700+ npm downloads 10,000+ on Docker Hub 3,400+...
» more
Licensing and pricing modelsHarperDB follows a freemium/premium model . A data base is only as powerful as it...
» more

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More resources
FatDBGoogle Cloud FirestoreHarperDBSpark SQL
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