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DBMS > Apache IoTDB vs. Splice Machine vs. Yanza

System Properties Comparison Apache IoTDB vs. Splice Machine vs. Yanza

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonSplice Machine  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines 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 FlinkOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkTime Series DBMS for IoT Applications
Primary database modelTime Series DBMSRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.13
Rank#199  Overall
#16  Time Series DBMS
Score0.54
Rank#265  Overall
#120  Relational DBMS
Websiteiotdb.apache.orgsplicemachine.comyanza.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlsplicemachine.com/­how-it-works
DeveloperApache Software FoundationSplice MachineYanza
Initial release201820142015
Current release1.1.0, April 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoAGPL 3.0, commercial license availablecommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenonono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Solaris
Windows
Windows
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesno
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.nono
Secondary indexesyesyesno
SQL infoSupport of SQLSQL-like query languageyesno
APIs and other access methodsJDBC
Native API
JDBC
Native Spark Datasource
ODBC
HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
any language that supports HTTP calls
Server-side scripts infoStored proceduresyesyes infoJavano
Triggersyesyesyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparkYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlyesAccess rights for users, groups and roles according to SQL-standardno

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More resources
Apache IoTDBSplice MachineYanza
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