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DBMS > Apache IoTDB vs. HugeGraph vs. Kinetica vs. Oracle NoSQL

System Properties Comparison Apache IoTDB vs. HugeGraph vs. Kinetica vs. Oracle NoSQL

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHugeGraph  Xexclude from comparisonKinetica  Xexclude from comparisonOracle NoSQL  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 fast-speed and highly-scalable Graph DBMSFully vectorized database across both GPUs and CPUsA multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes
Primary database modelTime Series DBMSGraph DBMSRelational DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score2.95
Rank#100  Overall
#17  Document stores
#17  Key-value stores
#50  Relational DBMS
Websiteiotdb.apache.orggithub.com/­hugegraph
hugegraph.apache.org
www.kinetica.comwww.oracle.com/­database/­nosql/­technologies/­nosql
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlhugegraph.apache.org/­docsdocs.kinetica.comdocs.oracle.com/­en/­database/­other-databases/­nosql-database/­index.html
DeveloperApache Software FoundationBaiduKineticaOracle
Initial release2018201820122011
Current release1.1.0, April 20230.97.1, August 202123.3, December 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0commercialOpen Source infoProprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC, C++Java
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
macOS
Unix
LinuxLinux
Solaris SPARC/x86
Data schemeyesyesyesSupport Fixed schema and Schema-less deployment with the ability to interoperate between them.
Typing infopredefined data types such as float or dateyesyesyesoptional
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 indexesyesyes infoalso supports composite index and range indexyesyes
SQL infoSupport of SQLSQL-like query languagenoSQL-like DML and DDL statementsSQL-like DML and DDL statements
APIs and other access methodsJDBC
Native API
Java API
RESTful HTTP API
TinkerPop Gremlin
JDBC
ODBC
RESTful HTTP API
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Groovy
Java
Python
C++
Java
JavaScript (Node.js)
Python
C
C#
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesasynchronous Gremlin script jobsuser defined functionsno
Triggersyesnoyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)yes infodepending on used storage backend, e.g. Cassandra and HBaseShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyes infodepending on used storage backend, e.g. Cassandra and HBaseSource-replica replicationElectable source-replica replication per shard. Support distributed global deployment with Multi-region table feature
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkvia hugegraph-sparknowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency infodepending on configuration
Foreign keys infoReferential integritynoyes infoedges in graphyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoconfigurable infoACID within a storage node (=shard)
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.yesyesyes infoGPU vRAM or System RAMyes infooff heap cache
User concepts infoAccess controlyesUsers, roles and permissionsAccess rights for users and roles on table levelAccess rights for users and roles

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More resources
Apache IoTDBHugeGraphKineticaOracle NoSQL
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