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DBMS > FatDB vs. Google Cloud Firestore vs. Informix vs. Spark SQL vs. Teradata Aster

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

Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonInformix  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata Aster  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines 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 dataSpark SQL is a component on top of 'Spark Core' for structured data processingPlatform for big data analytics on multistructured data sources and types
Primary database modelDocument store
Key-value store
Document storeRelational DBMS infoSince Version 12.10 support for JSON/BSON datatypes compatible with MongoDBRelational DBMSRelational 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
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitefirebase.google.com/­products/­firestorewww.ibm.com/­products/­informixspark.apache.org/­sql
Technical documentationfirebase.google.com/­docs/­firestoreinformix.hcldoc.com
www.ibm.com/­support/­knowledgecenter/­SSGU8G/­welcomeIfxServers.html
spark.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 FoundationTeradata
Initial release20122017198420142005
Current release14.10.FC5, November 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercialcommercial infofree developer edition availableOpen Source infoApache 2.0commercial
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#C, C++ and JavaScala
Server operating systemsWindowshostedAIX
HP-UX
Linux
macOS
Solaris
Windows
Linux
OS X
Windows
Linux
Data schemeschema-freeschema-freeyesyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesyesyes infoSince Version 12.10 support for JSON/BSON datatypesyesyes
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.nonoyes infoin Aster File Store
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLno infoVia inetgration in SQL ServernoyesSQL-like DML and DDL statementsyes
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
JDBC
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC#Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyes infovia applicationsyes, Firebase Rules & Cloud FunctionsyesnoR packages
Triggersyes infovia applicationsyes, with Cloud Functionsyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replicationMulti-source replication
Source-replica replication
noneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesUsing Cloud Dataflownoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACIDnoACID
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 controlsnofine grained access rights according to SQL-standard

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More resources
FatDBGoogle Cloud FirestoreInformixSpark SQLTeradata Aster
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