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DBMS > HugeGraph vs. Kinetica vs. Oracle Berkeley DB vs. Splice Machine

System Properties Comparison HugeGraph vs. Kinetica vs. Oracle Berkeley DB vs. Splice Machine

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Editorial information provided by DB-Engines
NameHugeGraph  Xexclude from comparisonKinetica  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionA fast-speed and highly-scalable Graph DBMSFully vectorized database across both GPUs and CPUsWidely used in-process key-value storeOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelGraph DBMSRelational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMS
Secondary database modelsSpatial 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
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitegithub.com/­hugegraph
hugegraph.apache.org
www.kinetica.comwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlsplicemachine.com
Technical documentationhugegraph.apache.org/­docsdocs.kinetica.comdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlsplicemachine.com/­how-it-works
DeveloperBaiduKineticaOracle infooriginally developed by Sleepycat, which was acquired by OracleSplice Machine
Initial release2018201219942014
Current release0.97.1, August 202118.1.40, May 20203.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infocommercial license availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++C, Java, C++ (depending on the Berkeley DB edition)Java
Server operating systemsLinux
macOS
Unix
LinuxAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.nonoyes infoonly with the Berkeley DB XML edition
Secondary indexesyes infoalso supports composite index and range indexyesyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyes infoSQL interfaced based on SQLite is availableyes
APIs and other access methodsJava API
RESTful HTTP API
TinkerPop Gremlin
JDBC
ODBC
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesGroovy
Java
Python
C++
Java
JavaScript (Node.js)
Python
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresasynchronous Gremlin script jobsuser defined functionsnoyes infoJava
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infoonly for the SQL APIyes
Partitioning methods infoMethods for storing different data on different nodesyes infodepending on used storage backend, e.g. Cassandra and HBaseShardingnoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infodepending on used storage backend, e.g. Cassandra and HBaseSource-replica replicationSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsvia hugegraph-sparknonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyes infoedges in graphyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
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.yesyes infoGPU vRAM or System RAMyesyes
User concepts infoAccess controlUsers, roles and permissionsAccess rights for users and roles on table levelnoAccess rights for users, groups and roles according to SQL-standard

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More resources
HugeGraphKineticaOracle Berkeley DBSplice Machine
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