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DBMS > HugeGraph vs. IRONdb vs. Kinetica vs. NSDb vs. TimesTen

System Properties Comparison HugeGraph vs. IRONdb vs. Kinetica vs. NSDb vs. TimesTen

Editorial information provided by DB-Engines
NameHugeGraph  Xexclude from comparisonIRONdb  Xexclude from comparisonKinetica  Xexclude from comparisonNSDb  Xexclude from comparisonTimesTen  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA fast-speed and highly-scalable Graph DBMSA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityFully vectorized database across both GPUs and CPUsScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesIn-Memory RDBMS compatible to Oracle
Primary database modelGraph DBMSTime Series DBMSRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score1.31
Rank#163  Overall
#74  Relational DBMS
Websitegithub.com/­hugegraph
hugegraph.apache.org
www.circonus.com/solutions/time-series-database/www.kinetica.comnsdb.iowww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationhugegraph.apache.org/­docsdocs.circonus.com/irondb/category/getting-starteddocs.kinetica.comnsdb.io/­Architecturedocs.oracle.com/­database/­timesten-18.1
DeveloperBaiduCirconus LLC.KineticaOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20182017201220171998
Current release0.9V0.10.20, January 20187.1, August 202111 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC and C++C, C++Java, Scala
Server operating systemsLinux
macOS
Unix
LinuxLinuxLinux
macOS
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsyesyes: int, bigint, decimal, stringyes
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.nonononono
Secondary indexesyes infoalso supports composite index and range indexnoyesall fields are automatically indexedyes
SQL infoSupport of SQLnoSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like DML and DDL statementsSQL-like query languageyes
APIs and other access methodsJava API
RESTful HTTP API
TinkerPop Gremlin
HTTP APIJDBC
ODBC
RESTful HTTP API
gRPC
HTTP REST
WebSocket
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesGroovy
Java
Python
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C++
Java
JavaScript (Node.js)
Python
Java
Scala
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresasynchronous Gremlin script jobsyes, in Luauser defined functionsnoPL/SQL
Triggersnonoyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesyes infodepending on used storage backend, e.g. Cassandra and HBaseAutomatic, metric affinity per nodeShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infodepending on used storage backend, e.g. Cassandra and HBaseconfigurable replication factor, datacenter awareSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsvia hugegraph-sparknononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate Consistency or Eventual Consistency depending on configurationEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infoedges in graphnoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesUsing Apache Luceneyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlUsers, roles and permissionsnoAccess rights for users and roles on table levelfine grained access rights according to SQL-standard

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More resources
HugeGraphIRONdbKineticaNSDbTimesTen
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