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DBMS > Apache IoTDB vs. Citus vs. Databricks vs. Firebase Realtime Database

System Properties Comparison Apache IoTDB vs. Citus vs. Databricks vs. Firebase Realtime Database

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonCitus  Xexclude from comparisonDatabricks  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparison
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 FlinkScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.
Primary database modelTime Series DBMSRelational DBMSDocument store
Relational DBMS
Document store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#159  Overall
#14  Time Series DBMS
Score2.13
Rank#117  Overall
#56  Relational DBMS
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score13.60
Rank#39  Overall
#6  Document stores
Websiteiotdb.apache.orgwww.citusdata.comwww.databricks.comfirebase.google.com/­products/­realtime-database
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.citusdata.comdocs.databricks.comfirebase.google.com/­docs/­database
DeveloperApache Software FoundationDatabricksGoogle infoacquired by Google 2014
Initial release2018201020132012
Current release1.1.0, April 20238.1, December 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoAGPL, commercial license also availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC
Server operating systemsAll OS with a Java VM (>= 1.8)Linuxhostedhosted
Data schemeyesyesFlexible Schema (defined schema, partial schema, schema free)schema-free
Typing infopredefined data types such as float or dateyesyesyes
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.noyes infospecific XML type available, but no XML query functionalityyesno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languageyes infostandard, with numerous extensionswith Databricks SQLno
APIs and other access methodsJDBC
Native API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
RESTful HTTP API
Android
iOS
JavaScript API
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Python
R
Scala
Java
JavaScript
Objective-C
Server-side scripts infoStored proceduresyesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.user defined functions and aggregateslimited functionality with using 'rules'
TriggersyesyesCallbacks are triggered when data changes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasSource-replica replication infoother methods possible by using 3rd party extensionsyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDyes
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.yesnono
User concepts infoAccess controlyesfine grained access rights according to SQL-standardyes, based on authentication and database rules
More information provided by the system vendor
Apache IoTDBCitusDatabricksFirebase Realtime Database
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Apache IoTDBCitusDatabricksFirebase Realtime Database
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