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DBMS > FatDB vs. Google Cloud Firestore vs. Informix vs. LokiJS vs. Spark SQL

System Properties Comparison FatDB vs. Google Cloud Firestore vs. Informix vs. LokiJS vs. Spark SQL

Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonInformix  Xexclude from comparisonLokiJS  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 secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things dataIn-memory JavaScript DBMSSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Document storeRelational DBMS infoSince Version 12.10 support for JSON/BSON datatypes compatible with MongoDBDocument storeRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS infowith Informix TimeSeries Extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.36
Rank#53  Overall
#9  Document stores
Score17.12
Rank#34  Overall
#21  Relational DBMS
Score0.49
Rank#260  Overall
#42  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitefirebase.google.com/­products/­firestorewww.ibm.com/­products/­informixgithub.com/­techfort/­LokiJSspark.apache.org/­sql
Technical documentationfirebase.google.com/­docs/­firestoreinformix.hcldoc.com
www.ibm.com/­support/­knowledgecenter/­SSGU8G/­welcomeIfxServers.html
techfort.github.io/­LokiJSspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFatCloudGoogleIBM, HCL Technologies infoEffective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.Apache Software Foundation
Initial release20122017198420142014
Current release14.10.FC5, November 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercialcommercial infofree developer edition availableOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#C, C++ and JavaJavaScriptScala
Server operating systemsWindowshostedAIX
HP-UX
Linux
macOS
Solaris
Windows
server-less, requires a JavaScript environment (browser, Node.js)Linux
OS X
Windows
Data schemeschema-freeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes infoSince Version 12.10 support for JSON/BSON datatypesnoyes
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 indexesyesyesyesyes infovia viewsno
SQL infoSupport of SQLno infoVia inetgration in SQL ServernoyesnoSQL-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
JSON API infoMongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JavaScript APIJDBC
ODBC
Supported programming languagesC#Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaScriptJava
Python
R
Scala
Server-side scripts infoStored proceduresyes infovia applicationsyes, Firebase Rules & Cloud FunctionsyesView functions in JavaScriptno
Triggersyes infovia applicationsyes, with Cloud Functionsyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replicationMulti-source replication
Source-replica replication
nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesUsing Cloud Dataflownoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistencynone
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACIDno infoatomic operations within a single collection possibleno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoSerialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
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.Users with fine-grained authentication, authorization, and auditing controlsnono

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More resources
FatDBGoogle Cloud FirestoreInformixLokiJSSpark SQL
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