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DBMS > Apache IoTDB vs. Kinetica vs. Riak TS vs. Spark SQL

System Properties Comparison Apache IoTDB vs. Kinetica vs. Riak TS vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonKinetica  Xexclude from comparisonRiak TS  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA lightweight IoT native database management system deployable on the device and syncing the collected data with the cloud and integrated with Hadoop and SparkFully vectorized database across both GPUs and CPUsRiak TS is a distributed NoSQL database optimized for time series data and based on Riak KVSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelTime Series DBMSRelational DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.42
Rank#253  Overall
#20  Time Series DBMS
Score0.66
Rank#212  Overall
#103  Relational DBMS
Score0.25
Rank#281  Overall
#24  Time Series DBMS
Score22.86
Rank#35  Overall
#21  Relational DBMS
Websiteiotdb.apache.orgwww.kinetica.comriak.com/­products/­riak-tsspark.apache.org/­sql
Technical documentationwww.kinetica.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationKineticaBasho TechnologiesApache Software Foundation
Initial release2018201220152014
Current release7.1, August 20213.2.0, October 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, C++ErlangScala
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinux
OS X
Linux
OS X
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.nononono
Secondary indexesyesyesrestrictedno
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statementsnoSQL-like DML and DDL statements
APIs and other access methodsJDBCJDBC
ODBC
RESTful HTTP API
HTTP API
Native Erlang Interface
JDBC
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Java
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functionsJavaScript and Erlangno
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency with synchronizing with the cloudImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Foreign keys infoReferential integritynoyesno infolinks between datasets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononono
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.yesyes infoGPU vRAM or System RAMno
User concepts infoAccess controlnoAccess rights for users and roles on table levelnono
More information provided by the system vendor
Apache IoTDBKineticaRiak TSSpark SQL
Specific characteristicsNative and fully vectorized database across both GPUs and CPUs, with memory first...
» more
Competitive advantagesBest in class geospatial and temporal analytics. Lockless architecture provides real-time...
» more
Typical application scenariosAny application requiring (1) real time insights, (2) time series analysis (3) geospatial...
» more
Key customersCitibank, US Air Force, Softbank, OVO, Telkomsel, USPS, 2 of the top 3 US Telcos,...
» more
Market metricsThe largest IoT deployment in the world, NORAD, runs on Kinetica.
» more
Licensing and pricing modelsAlways Free Tier in the Cloud, Pay-As-You-Go Consumption Based Pricing, and Portable...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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3rd partiesSQLFlow: Provides a visual representation of the overall flow of data. Automated SQL data lineage analysis across Databases, ETL, Business Intelligence, Cloud and Hadoop environments by parsing SQL Script and stored procedure.
» more

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More resources
Apache IoTDBKineticaRiak TSSpark SQL
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