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

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

Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonGridGain  Xexclude from comparisonInformix  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.GridGain is an in-memory computing platform, built on Apache IgniteA secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things dataSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Document storeKey-value store
Relational DBMS
Relational DBMS infoSince Version 12.10 support for JSON/BSON datatypes compatible with MongoDBRelational 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
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score17.12
Rank#34  Overall
#21  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitefirebase.google.com/­products/­firestorewww.gridgain.comwww.ibm.com/­products/­informixspark.apache.org/­sql
Technical documentationfirebase.google.com/­docs/­firestorewww.gridgain.com/­docs/­index.htmlinformix.hcldoc.com
www.ibm.com/­support/­knowledgecenter/­SSGU8G/­welcomeIfxServers.html
spark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFatCloudGoogleGridGain Systems, Inc.IBM, 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 release20122017200719842014
Current releaseGridGain 8.5.114.10.FC5, November 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial infofree developer edition availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#Java, C++, .NetC, C++ and JavaScala
Server operating systemsWindowshostedLinux
OS X
Solaris
Windows
AIX
HP-UX
Linux
macOS
Solaris
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes infoSince Version 12.10 support for JSON/BSON datatypesyes
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 indexesyesyesyesyesno
SQL infoSupport of SQLno infoVia inetgration in SQL ServernoANSI-99 for query and DML statements, subset of DDLyesSQL-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
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
JSON API infoMongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languagesC#Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infovia applicationsyes, Firebase Rules & Cloud Functionsyes (compute grid and cache interceptors can be used instead)yesno
Triggersyes infovia applicationsyes, with Cloud Functionsyes (cache interceptors and events)yesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replicationyes (replicated cache)Multi-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesUsing Cloud Dataflowyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACIDACIDno
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.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.Security Hooks for custom implementationsUsers with fine-grained authentication, authorization, and auditing controlsno

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More resources
FatDBGoogle Cloud FirestoreGridGainInformixSpark SQL
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