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DBMS > Apache IoTDB vs. Firebase Realtime Database vs. Microsoft Azure SQL Database vs. Trino

System Properties Comparison Apache IoTDB vs. Firebase Realtime Database vs. Microsoft Azure SQL Database vs. Trino

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonTrino  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 FlinkCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Database as a Service offering with high compatibility to Microsoft SQL ServerFast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL
Primary database modelTime Series DBMSDocument storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Document store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#159  Overall
#14  Time Series DBMS
Score13.60
Rank#39  Overall
#6  Document stores
Score72.95
Rank#16  Overall
#11  Relational DBMS
Score5.28
Rank#61  Overall
#35  Relational DBMS
Websiteiotdb.apache.orgfirebase.google.com/­products/­realtime-databaseazure.microsoft.com/­en-us/­products/­azure-sql/­databasetrino.io
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlfirebase.google.com/­docs/­databasedocs.microsoft.com/­en-us/­azure/­azure-sqltrino.io/­broadcast
trino.io/­docs/­current
DeveloperApache Software FoundationGoogle infoacquired by Google 2014MicrosoftTrino Software Foundation
Initial release2018201220102012 info2020 rebranded from PrestoSQL
Current release1.1.0, April 2023V12
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++Java
Server operating systemsAll OS with a Java VM (>= 1.8)hostedhostedLinux
macOS infofor devlopment
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonoyesno
Secondary indexesyesyesyesdepending on connected data-source
SQL infoSupport of SQLSQL-like query languagenoyesyes
APIs and other access methodsJDBC
Native API
Android
iOS
JavaScript API
RESTful HTTP API
ADO.NET
JDBC
ODBC
JDBC
RESTful HTTP API
Trino CLI
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Java
JavaScript
Objective-C
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
JavaScript (Node.js)
Python
R
Ruby
Server-side scripts infoStored proceduresyeslimited functionality with using 'rules'Transact SQLyes, depending on connected data-source
TriggersyesCallbacks are triggered when data changesyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)depending on connected data-source
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyes, with always 3 replicas availabledepending on connected data-source
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate Consistencydepending on connected data-source
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACIDdepending on connected data-source
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesdepending on connected data-source
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes
User concepts infoAccess controlyesyes, based on authentication and database rulesfine grained access rights according to SQL-standardSQL standard access control
More information provided by the system vendor
Apache IoTDBFirebase Realtime DatabaseMicrosoft Azure SQL Database infoformerly SQL AzureTrino
News

23 is a go, keeping pace with Java
17 September 2024

65: Performance boosts
12 September 2024

64: Control with Open Policy Agent OPA
22 August 2024

63: Querying with JS
1 August 2024

62: A lakehouse that simply works at Prezi
11 July 2024

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More resources
Apache IoTDBFirebase Realtime DatabaseMicrosoft Azure SQL Database infoformerly SQL AzureTrino
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