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DBMS > Apache IoTDB vs. JanusGraph vs. Kinetica vs. Riak TS

System Properties Comparison Apache IoTDB vs. JanusGraph vs. Kinetica vs. Riak TS

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonKinetica  Xexclude from comparisonRiak TS  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 SparkA Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017Fully vectorized database across both GPUs and CPUsRiak TS is a distributed NoSQL database optimized for time series data and based on Riak KV
Primary database modelTime Series DBMSGraph DBMSRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.42
Rank#253  Overall
#20  Time Series DBMS
Score2.43
Rank#118  Overall
#8  Graph DBMS
Score0.66
Rank#212  Overall
#103  Relational DBMS
Score0.25
Rank#281  Overall
#24  Time Series DBMS
Websiteiotdb.apache.orgjanusgraph.orgwww.kinetica.comriak.com/­products/­riak-ts
Technical documentationdocs.janusgraph.orgwww.kinetica.com/­docs
DeveloperApache Software FoundationLinux Foundation; originally developed as Titan by AureliusKineticaBasho Technologies
Initial release2018201720122015
Current release0.6.1, January 20227.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0commercialOpen Source
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC, C++Erlang
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Unix
Windows
LinuxLinux
OS X
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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 indexesyesyesyesrestricted
SQL infoSupport of SQLSQL-like query languagenoSQL-like DML and DDL statementsno
APIs and other access methodsJDBCJava API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
JDBC
ODBC
RESTful HTTP API
HTTP API
Native Erlang Interface
Supported programming languagesClojure
Java
Python
C++
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
Server-side scripts infoStored proceduresnoyesuser defined functionsJavaScript and Erlang
Triggersnoyesyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)ShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyes infovia Faunus, a graph analytics enginenoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency with synchronizing with the cloudEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Foreign keys infoReferential integritynoyes infoRelationships in graphsyesno infolinks between datasets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAM
User concepts infoAccess controlnoUser authentification and security via Rexster Graph ServerAccess rights for users and roles on table levelno
More information provided by the system vendor
Apache IoTDBJanusGraph infosuccessor of TitanKineticaRiak TS
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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More resources
Apache IoTDBJanusGraph infosuccessor of TitanKineticaRiak TS
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