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DBMS > Apache IoTDB vs. FatDB vs. Firebase Realtime Database vs. Graphite vs. Spark SQL

System Properties Comparison Apache IoTDB vs. FatDB vs. Firebase Realtime Database vs. Graphite vs. Spark SQL

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonFatDB  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGraphite  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.
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkA .NET NoSQL DBMS that can integrate with and extend SQL Server.Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Data logging and graphing tool for time series data infoThe storage layer (fixed size database) is called WhisperSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelTime Series DBMSDocument store
Key-value store
Document storeTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score14.29
Rank#39  Overall
#6  Document stores
Score4.57
Rank#73  Overall
#5  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteiotdb.apache.orgfirebase.google.com/­products/­realtime-databasegithub.com/­graphite-project/­graphite-webspark.apache.org/­sql
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlfirebase.google.com/­docs/­databasegraphite.readthedocs.iospark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationFatCloudGoogle infoacquired by Google 2014Chris DavisApache Software Foundation
Initial release20182012201220062014
Current release1.1.0, April 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoApache 2.0Open 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#PythonScala
Server operating systemsAll OS with a Java VM (>= 1.8)WindowshostedLinux
Unix
Linux
OS X
Windows
Data schemeyesschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesNumeric data onlyyes
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.nononono
Secondary indexesyesyesyesnono
SQL infoSupport of SQLSQL-like query languageno infoVia inetgration in SQL ServernonoSQL-like DML and DDL statements
APIs and other access methodsJDBC
Native API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Android
iOS
JavaScript API
RESTful HTTP API
HTTP API
Sockets
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#Java
JavaScript
Objective-C
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesyes infovia applicationslimited functionality with using 'rules'nono
Triggersyesyes infovia applicationsCallbacks are triggered when data changesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasselectable replication factornonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Immediate Consistency
Eventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
none
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoyesnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infolockingyes
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.yesno
User concepts infoAccess controlyesno infoCan implement custom security layer via applicationsyes, based on authentication and database rulesnono

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More resources
Apache IoTDBFatDBFirebase Realtime DatabaseGraphiteSpark SQL
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