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DBMS > Apache Pinot vs. FatDB vs. Google Cloud Firestore vs. Informix vs. Spark SQL

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

Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Firestore  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.
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyA .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 processing
Primary database modelRelational DBMSDocument store
Key-value store
Document storeRelational 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
Score0.38
Rank#275  Overall
#126  Relational DBMS
Score7.36
Rank#53  Overall
#9  Document stores
Score17.12
Rank#34  Overall
#21  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitepinot.apache.orgfirebase.google.com/­products/­firestorewww.ibm.com/­products/­informixspark.apache.org/­sql
Technical documentationdocs.pinot.apache.orgfirebase.google.com/­docs/­firestoreinformix.hcldoc.com
www.ibm.com/­support/­knowledgecenter/­SSGU8G/­welcomeIfxServers.html
spark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation and contributorsFatCloudGoogleIBM, 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 release20152012201719842014
Current release1.0.0, September 202314.10.FC5, November 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercial infofree developer edition availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC#C, C++ and JavaScala
Server operating systemsAll OS with a Java JDK11 or higherWindowshostedAIX
HP-UX
Linux
macOS
Solaris
Windows
Linux
OS X
Windows
Data schemeyesschema-freeschema-freeyesyes
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.nono
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like query languageno infoVia inetgration in SQL ServernoyesSQL-like DML and DDL statements
APIs and other access methodsJDBC.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
Supported programming languagesGo
Java
Python
C#Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infovia applicationsyes, Firebase Rules & Cloud Functionsyesno
Triggersyes infovia applicationsyes, with Cloud Functionsyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replicationMulti-source replication
Source-replica replication
none
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 integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
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.Users with fine-grained authentication, authorization, and auditing controlsno

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More resources
Apache PinotFatDBGoogle Cloud FirestoreInformixSpark SQL
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