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DBMS > FatDB vs. Google Cloud Firestore vs. Informix vs. Microsoft Azure Data Explorer vs. Spark SQL

System Properties Comparison FatDB vs. Google Cloud Firestore vs. Informix vs. Microsoft Azure Data Explorer vs. Spark SQL

Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonInformix  Xexclude from comparisonMicrosoft Azure Data Explorer  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 dataFully managed big data interactive analytics platformSpark 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 MongoDBRelational DBMS infocolumn orientedRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS infowith Informix TimeSeries Extension
Document store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
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
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitefirebase.google.com/­products/­firestorewww.ibm.com/­products/­informixazure.microsoft.com/­services/­data-explorerspark.apache.org/­sql
Technical documentationfirebase.google.com/­docs/­firestoreinformix.hcldoc.com
www.ibm.com/­support/­knowledgecenter/­SSGU8G/­welcomeIfxServers.html
docs.microsoft.com/­en-us/­azure/­data-explorerspark.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.MicrosoftApache Software Foundation
Initial release20122017198420192014
Current release14.10.FC5, November 2020cloud service with continuous releases3.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercialcommercial infofree developer edition availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#C, C++ and JavaScala
Server operating systemsWindowshostedAIX
HP-UX
Linux
macOS
Solaris
Windows
hostedLinux
OS X
Windows
Data schemeschema-freeschema-freeyesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyesyes infoSince Version 12.10 support for JSON/BSON datatypesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-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.noyesno
Secondary indexesyesyesyesall fields are automatically indexedno
SQL infoSupport of SQLno infoVia inetgration in SQL ServernoyesKusto Query Language (KQL), SQL subsetSQL-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
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
Supported programming languagesC#Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infovia applicationsyes, Firebase Rules & Cloud FunctionsyesYes, possible languages: KQL, Python, Rno
Triggersyes infovia applicationsyes, with Cloud Functionsyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infoImplicit feature of the cloud serviceyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replicationMulti-source replication
Source-replica replication
yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesUsing Cloud DataflownoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
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 controlsAzure Active Directory Authenticationno

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More resources
FatDBGoogle Cloud FirestoreInformixMicrosoft Azure Data ExplorerSpark SQL
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