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DBMS > Apache IoTDB vs. JanusGraph vs. Kinetica vs. Microsoft Azure SQL Database vs. TinkerGraph

System Properties Comparison Apache IoTDB vs. JanusGraph vs. Kinetica vs. Microsoft Azure SQL Database vs. TinkerGraph

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonTinkerGraph  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 FlinkA 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 CPUsDatabase as a Service offering with high compatibility to Microsoft SQL ServerA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API
Primary database modelTime Series DBMSGraph DBMSRelational DBMSRelational DBMSGraph 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
Score1.94
Rank#129  Overall
#12  Graph DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score0.08
Rank#348  Overall
#35  Graph DBMS
Websiteiotdb.apache.orgjanusgraph.orgwww.kinetica.comazure.microsoft.com/­en-us/­products/­azure-sql/­databasetinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlin
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.janusgraph.orgdocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­azure-sql
DeveloperApache Software FoundationLinux Foundation; originally developed as Titan by AureliusKineticaMicrosoft
Initial release20182017201220102009
Current release1.1.0, April 20230.6.3, February 20237.1, August 2021V12
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0commercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC, C++C++Java
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Unix
Windows
Linuxhosted
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.nononoyesno
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLSQL-like query languagenoSQL-like DML and DDL statementsyesno
APIs and other access methodsJDBC
Native API
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
TinkerPop 3
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Clojure
Java
Python
C++
Java
JavaScript (Node.js)
Python
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
Groovy
Java
Server-side scripts infoStored proceduresyesyesuser defined functionsTransact SQLno
Triggersyesyesyes infotriggers when inserted values for one or more columns fall within a specified rangeyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)yes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)Shardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesSource-replica replicationyes, with always 3 replicas availablenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyes infovia Faunus, a graph analytics enginenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on configurationImmediate Consistencynone
Foreign keys infoReferential integritynoyes infoRelationships in graphsyesyesyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesno
Durability infoSupport for making data persistentyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyesyesoptional
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlyesUser authentification and security via Rexster Graph ServerAccess rights for users and roles on table levelfine grained access rights according to SQL-standardno

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More resources
Apache IoTDBJanusGraph infosuccessor of TitanKineticaMicrosoft Azure SQL Database infoformerly SQL AzureTinkerGraph
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