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DBMS > Apache IoTDB vs. FatDB vs. Microsoft Azure SQL Database vs. Splice Machine

System Properties Comparison Apache IoTDB vs. FatDB vs. Microsoft Azure SQL Database vs. Splice Machine

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonFatDB  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonSplice Machine  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.Database as a Service offering with high compatibility to Microsoft SQL ServerOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelTime Series DBMSDocument store
Key-value store
Relational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteiotdb.apache.orgazure.microsoft.com/­en-us/­products/­azure-sql/­databasesplicemachine.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.microsoft.com/­en-us/­azure/­azure-sqlsplicemachine.com/­how-it-works
DeveloperApache Software FoundationFatCloudMicrosoftSplice Machine
Initial release2018201220102014
Current release1.1.0, April 2023V123.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC#C++Java
Server operating systemsAll OS with a Java VM (>= 1.8)WindowshostedLinux
OS X
Solaris
Windows
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.noyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languageno infoVia inetgration in SQL Serveryesyes
APIs and other access methodsJDBC
Native API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
ADO.NET
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyesyes infovia applicationsTransact SQLyes infoJava
Triggersyesyes infovia applicationsyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShared Nothhing Auto-Sharding, Columnar 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 replicasselectable replication factoryes, with always 3 replicas availableMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparkyesnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
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.yesyes
User concepts infoAccess controlyesno infoCan implement custom security layer via applicationsfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache IoTDBFatDBMicrosoft Azure SQL Database infoformerly SQL AzureSplice Machine
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