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DBMS > HugeGraph vs. jBASE vs. Kinetica vs. NSDb vs. RavenDB

System Properties Comparison HugeGraph vs. jBASE vs. Kinetica vs. NSDb vs. RavenDB

Editorial information provided by DB-Engines
NameHugeGraph  Xexclude from comparisonjBASE  Xexclude from comparisonKinetica  Xexclude from comparisonNSDb  Xexclude from comparisonRavenDB  Xexclude from comparison
DescriptionA fast-speed and highly-scalable Graph DBMSA robust multi-value DBMS comprising development tools and middlewareFully vectorized database across both GPUs and CPUsScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesOpen Source Operational and Transactional Enterprise NoSQL Document Database
Primary database modelGraph DBMSMultivalue DBMSRelational DBMSTime Series DBMSDocument store
Secondary database modelsSpatial DBMS
Time Series DBMS
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score1.49
Rank#156  Overall
#3  Multivalue DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.08
Rank#369  Overall
#40  Time Series DBMS
Score2.84
Rank#101  Overall
#18  Document stores
Websitegithub.com/­hugegraph
hugegraph.apache.org
www.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-jbasewww.kinetica.comnsdb.ioravendb.net
Technical documentationhugegraph.apache.org/­docsdocs.rocketsoftware.com/­bundle?labelkey=jbase_5.9docs.kinetica.comnsdb.io/­Architectureravendb.net/­docs
DeveloperBaiduRocket Software (formerly Zumasys)KineticaHibernating Rhinos
Initial release20181991201220172010
Current release0.95.77.1, August 20215.4, July 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoApache Version 2.0Open Source infoAGPL version 3, commercial license available
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, C++Java, ScalaC#
Server operating systemsLinux
macOS
Unix
AIX
Linux
Windows
LinuxLinux
macOS
Linux
macOS
Raspberry Pi
Windows
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesoptionalyesyes: int, bigint, decimal, stringno
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.noyesnono
Secondary indexesyes infoalso supports composite index and range indexyesall fields are automatically indexedyes
SQL infoSupport of SQLnoEmbedded SQL for jBASE in BASICSQL-like DML and DDL statementsSQL-like query languageSQL-like query language (RQL)
APIs and other access methodsJava API
RESTful HTTP API
TinkerPop Gremlin
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API
JDBC
ODBC
RESTful HTTP API
gRPC
HTTP REST
WebSocket
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Supported programming languagesGroovy
Java
Python
.Net
Basic
Jabbascript
Java
C++
Java
JavaScript (Node.js)
Python
Java
Scala
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresasynchronous Gremlin script jobsyesuser defined functionsnoyes
Triggersnoyesyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesyes infodepending on used storage backend, e.g. Cassandra and HBaseShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infodepending on used storage backend, e.g. Cassandra and HBaseyesSource-replica replicationMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsvia hugegraph-sparknononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integrityyes infoedges in graphnoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonoACID, Cluster-wide transaction available
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesUsing Apache Luceneyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlUsers, roles and permissionsAccess rights can be defined down to the item levelAccess rights for users and roles on table levelAuthorization levels configured per client per database

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More resources
HugeGraphjBASEKineticaNSDbRavenDB
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