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DBMS > GridGain vs. HugeGraph vs. Kinetica

System Properties Comparison GridGain vs. HugeGraph vs. Kinetica

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Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonHugeGraph  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteA fast-speed and highly-scalable Graph DBMSFully vectorized database across both GPUs and CPUs
Primary database modelKey-value store
Relational DBMS
Graph DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.53
Rank#155  Overall
#26  Key-value stores
#73  Relational DBMS
Score0.15
Rank#339  Overall
#33  Graph DBMS
Score0.69
Rank#234  Overall
#107  Relational DBMS
Websitewww.gridgain.comgithub.com/­hugegraph
hugegraph.apache.org
www.kinetica.com
Technical documentationwww.gridgain.com/­docs/­index.htmlhugegraph.apache.org/­docsdocs.kinetica.com
DeveloperGridGain Systems, Inc.BaiduKinetica
Initial release200720182012
Current releaseGridGain 8.5.10.97.1, August 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .NetJavaC, C++
Server operating systemsLinux
OS X
Solaris
Windows
Linux
macOS
Unix
Linux
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.yesnono
Secondary indexesyesyes infoalso supports composite index and range indexyes
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLnoSQL-like DML and DDL statements
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Java API
RESTful HTTP API
TinkerPop Gremlin
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
Groovy
Java
Python
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)asynchronous Gremlin script jobsuser defined functions
Triggersyes (cache interceptors and events)noyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)yes infodepending on used storage backend, e.g. Cassandra and HBaseSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)via hugegraph-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyes infoedges in graphyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
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 controlSecurity Hooks for custom implementationsUsers, roles and permissionsAccess rights for users and roles on table level

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More resources
GridGainHugeGraphKinetica
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