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DBMS > Apache IoTDB vs. Kinetica vs. Microsoft Azure SQL Database vs. Spark SQL vs. Warp 10

System Properties Comparison Apache IoTDB vs. Kinetica vs. Microsoft Azure SQL Database vs. Spark SQL vs. Warp 10

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonSpark SQL  Xexclude from comparisonWarp 10  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 FlinkFully vectorized database across both GPUs and CPUsDatabase as a Service offering with high compatibility to Microsoft SQL ServerSpark SQL is a component on top of 'Spark Core' for structured data processingTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelTime Series DBMSRelational DBMSRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document 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
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.07
Rank#349  Overall
#32  Time Series DBMS
Websiteiotdb.apache.orgwww.kinetica.comazure.microsoft.com/­en-us/­products/­azure-sql/­databasespark.apache.org/­sqlwww.warp10.io
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­azure-sqlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.warp10.io/­content/­02_Getting_started
DeveloperApache Software FoundationKineticaMicrosoftApache Software FoundationSenX
Initial release20182012201020142015
Current release1.1.0, April 20237.1, August 2021V123.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoApache 2.0Open Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, C++C++ScalaJava
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxhostedLinux
OS X
Windows
Linux
OS X
Windows
Data schemeyesyesyesyesschema-free
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.nonoyesnono
Secondary indexesyesyesyesnono
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statementsyesSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
Native API
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
JDBC
ODBC
HTTP API
Jupyter
WebSocket
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C++
Java
JavaScript (Node.js)
Python
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesuser defined functionsTransact SQLnoyes infoWarpScript
Triggersyesyes infotriggers when inserted values for one or more columns fall within a specified rangeyesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardingyes, utilizing Spark CoreSharding infobased on HBase
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 replicationyes, with always 3 replicas availablenoneselectable replication factor infobased on HBase
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
Immediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency infobased on HBase
Foreign keys infoReferential integritynoyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.yesyes infoGPU vRAM or System RAMnoyes
User concepts infoAccess controlyesAccess rights for users and roles on table levelfine grained access rights according to SQL-standardnoMandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
Apache IoTDBKineticaMicrosoft Azure SQL Database infoformerly SQL AzureSpark SQLWarp 10
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