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DBMS > Apache IoTDB vs. DolphinDB vs. FatDB vs. Firebase Realtime Database vs. Graph Engine

System Properties Comparison Apache IoTDB vs. DolphinDB vs. FatDB vs. Firebase Realtime Database vs. Graph Engine

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDolphinDB  Xexclude from comparisonFatDB  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGraph Engine infoformer name: Trinity  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 FlinkDolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.A .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.A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine
Primary database modelTime Series DBMSTime Series DBMSDocument store
Key-value store
Document storeGraph DBMS
Key-value store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score4.03
Rank#78  Overall
#6  Time Series DBMS
Score13.64
Rank#39  Overall
#6  Document stores
Score0.67
Rank#232  Overall
#21  Graph DBMS
#34  Key-value stores
Websiteiotdb.apache.orgwww.dolphindb.comfirebase.google.com/­products/­realtime-databasewww.graphengine.io
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.dolphindb.cn/­en/­help200/­index.htmlfirebase.google.com/­docs/­databasewww.graphengine.io/­docs/­manual
DeveloperApache Software FoundationDolphinDB, IncFatCloudGoogle infoacquired by Google 2014Microsoft
Initial release20182018201220122010
Current release1.1.0, April 2023v2.00.4, January 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree community version availablecommercialcommercialOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C#.NET and C
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
Windows
Windowshosted.NET
Data schemeyesyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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 indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languageSQL-like query languageno infoVia inetgration in SQL Servernono
APIs and other access methodsJDBC
Native API
JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Android
iOS
JavaScript API
RESTful HTTP API
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
C#Java
JavaScript
Objective-C
C#
C++
F#
Visual Basic
Server-side scripts infoStored proceduresyesyesyes infovia applicationslimited functionality with using 'rules'yes
Triggersyesnoyes infovia applicationsCallbacks are triggered when data changesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioningShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnoyesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlyesAdministrators, Users, Groupsno infoCan implement custom security layer via applicationsyes, based on authentication and database rules

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More resources
Apache IoTDBDolphinDBFatDBFirebase Realtime DatabaseGraph Engine infoformer name: Trinity
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